|
[
|
|
"not-for-all-audiences",
|
|
"endpoints_compatible",
|
|
"transformers",
|
|
"pytorch",
|
|
"autotrain_compatible",
|
|
"text-generation-inference",
|
|
"tensorboard",
|
|
"safetensors",
|
|
"bert",
|
|
"generated_from_trainer",
|
|
"model-index",
|
|
"gpt2",
|
|
"gguf",
|
|
"tf",
|
|
"diffusers",
|
|
"roberta",
|
|
"wav2vec2",
|
|
"mergekit",
|
|
"distilbert",
|
|
"t5",
|
|
"llama",
|
|
"huggingtweets",
|
|
"lora",
|
|
"autotrain",
|
|
"imatrix",
|
|
"marian",
|
|
"deep-reinforcement-learning",
|
|
"mistral",
|
|
"evaluation",
|
|
"stable-diffusion",
|
|
"xlm-roberta",
|
|
"stable-baselines3",
|
|
"text-embeddings-inference",
|
|
"bart",
|
|
"custom_code",
|
|
"onnx",
|
|
"sentence-transformers",
|
|
"qwen2",
|
|
"flux",
|
|
"generated_from_keras_callback",
|
|
"LunarLander-v2",
|
|
"custom-implementation",
|
|
"pretraining",
|
|
"unsloth",
|
|
"electra",
|
|
"mt5",
|
|
"vision",
|
|
"chat",
|
|
"speech",
|
|
"trl",
|
|
"medical",
|
|
"q-learning",
|
|
"replicate",
|
|
"co2_eq_emissions",
|
|
"lazymergekit",
|
|
"llama-cpp",
|
|
"4-bit",
|
|
"vit",
|
|
"gguf-my-repo",
|
|
"hf-asr-leaderboard",
|
|
"biology",
|
|
"gemma2",
|
|
"lyrics",
|
|
"huggingartists",
|
|
"albert",
|
|
"legal",
|
|
"sft",
|
|
"robust-speech-event",
|
|
"stable-diffusion-xl",
|
|
"espnet",
|
|
"llama-3",
|
|
"tf-keras",
|
|
"camembert",
|
|
"causal-lm",
|
|
"meta",
|
|
"roleplay",
|
|
"pegasus",
|
|
"deberta-v2",
|
|
"multiberts",
|
|
"facebook",
|
|
"mbart",
|
|
"stable-diffusion-diffusers",
|
|
"exbert",
|
|
"peft",
|
|
"Taxi-v3",
|
|
"anime",
|
|
"whisper",
|
|
"FrozenLake-v1-4x4-no_slippery",
|
|
"8-bit",
|
|
"gpt_neo",
|
|
"xlsr-fine-tuning-week",
|
|
"instruct",
|
|
"encoder-decoder",
|
|
"qwen",
|
|
"chemistry",
|
|
"music",
|
|
"m2m_100",
|
|
"GGUF",
|
|
"spacy",
|
|
"lm-head",
|
|
"bitsandbytes",
|
|
"nsfw",
|
|
"huggingpics",
|
|
"autonlp",
|
|
"nlp",
|
|
"multimodal",
|
|
"vision-encoder-decoder",
|
|
"uncensored",
|
|
"mteb",
|
|
"adapter-transformers",
|
|
"axolotl",
|
|
"deep-rl-class",
|
|
"SpaceInvadersNoFrameskip-v4",
|
|
"deberta",
|
|
"reinforce",
|
|
"transformers.js",
|
|
"math",
|
|
"gptq",
|
|
"dpo",
|
|
"question generation",
|
|
"deep-narrow",
|
|
"llm",
|
|
"mpnet",
|
|
"fashion",
|
|
"speech-encoder-decoder",
|
|
"llava",
|
|
"nemo",
|
|
"mixtral",
|
|
"openvino",
|
|
"clip",
|
|
"roleplaying",
|
|
"rp",
|
|
"ecommerce",
|
|
"rust",
|
|
"llama-factory",
|
|
"chatml",
|
|
"exl2",
|
|
"qwen-coder",
|
|
"abliterated",
|
|
"image-generation",
|
|
"climate",
|
|
"hubert",
|
|
"codeqwen",
|
|
"timm",
|
|
"keras",
|
|
"segformer",
|
|
"webscraping",
|
|
"fashion product",
|
|
"fashion image",
|
|
"gptj",
|
|
"multi-modal",
|
|
"multi-task",
|
|
"PyTorch",
|
|
"xlnet",
|
|
"creative",
|
|
"reasoning",
|
|
"spanish",
|
|
"ml-agents",
|
|
"awq",
|
|
"5-bit",
|
|
"unispeech",
|
|
"imitation-learning",
|
|
"offline-reinforcement-learning",
|
|
"3-bit",
|
|
"6-bit",
|
|
"CartPole-v1",
|
|
"gpt4",
|
|
"japanese",
|
|
"unity-ml-agents",
|
|
"NER",
|
|
"bloom",
|
|
"stable-diffusion-xl-diffusers",
|
|
"classification",
|
|
"human-feedback",
|
|
"diffusers-training",
|
|
"model_for_talk",
|
|
"opus-mt-tc",
|
|
"llama-2",
|
|
"distillation",
|
|
"phi3",
|
|
"seq2seq",
|
|
"2-bit",
|
|
"TensorBlock",
|
|
"longformer",
|
|
"pony",
|
|
"rf100",
|
|
"writing",
|
|
"masked-lm",
|
|
"swin",
|
|
"roberta-base",
|
|
"bert_causalm",
|
|
"story",
|
|
"synthetic data",
|
|
"sentiment",
|
|
"benchmark",
|
|
"LLM",
|
|
"alpaca",
|
|
"style",
|
|
"embeddings",
|
|
"speechbrain",
|
|
"Transformer",
|
|
"fiction",
|
|
"bfloat16",
|
|
"opt",
|
|
"fastai",
|
|
"huggan",
|
|
"tabular_classification",
|
|
"coreml",
|
|
"controlnet",
|
|
"stanza",
|
|
"binary_classification",
|
|
"sequence-tagger-model",
|
|
"question-generation",
|
|
"ML-Agents-Pyramids",
|
|
"language",
|
|
"storytelling",
|
|
"wavlm",
|
|
"layoutlmv2",
|
|
"fuego",
|
|
"qwen2_vl",
|
|
"flair",
|
|
"dpr",
|
|
"CTC",
|
|
"dependency-parsing",
|
|
"lstm_causalm",
|
|
"gpt2_causalm",
|
|
"roberta_causalm",
|
|
"DFP",
|
|
"french prompts",
|
|
"science",
|
|
"RLHF",
|
|
"sequence-to-sequence",
|
|
"generic",
|
|
"function calling",
|
|
"migrated",
|
|
"instruction-finetuning",
|
|
"ocr",
|
|
"internvl_chat",
|
|
"full",
|
|
"pytorch_model_hub_mixin",
|
|
"unispeech-sat",
|
|
"creative-writing",
|
|
"fluxgym",
|
|
"vllm",
|
|
"teach-my-agent-parkour",
|
|
"resnet",
|
|
"model_hub_mixin",
|
|
"big_bird",
|
|
"creative writing",
|
|
"realistic",
|
|
"finetuned",
|
|
"fiction writing",
|
|
"italian",
|
|
"NeMo",
|
|
"rlfh",
|
|
"UCI",
|
|
"scene continue",
|
|
"NLP",
|
|
"horror",
|
|
"tflite",
|
|
"gpt",
|
|
"qa",
|
|
"sparsity",
|
|
"conditional-text-generation",
|
|
"story generation",
|
|
"nvidia",
|
|
"open_clip",
|
|
"fiction story",
|
|
"text generation",
|
|
"rlhf",
|
|
"Transformers",
|
|
"rlaif",
|
|
"plot generation",
|
|
"sub-plot generation",
|
|
"chatglm",
|
|
"photorealistic",
|
|
"plbart",
|
|
"florence2",
|
|
"tapas",
|
|
"AntBulletEnv-v0",
|
|
"Pixelcopter-PLE-v0",
|
|
"swearing",
|
|
"english",
|
|
"gpt_neox",
|
|
"images",
|
|
"physics",
|
|
"convnext",
|
|
"oBERT",
|
|
"internvl",
|
|
"vits",
|
|
"joblib",
|
|
"compression",
|
|
"chinese",
|
|
"ultra-realistic",
|
|
"compressed-tensors",
|
|
"alignment-handbook",
|
|
"finetuning",
|
|
"pruning",
|
|
"qwen2.5",
|
|
"orpo",
|
|
"llava_llama",
|
|
"llama-3.1",
|
|
"optimum_graphcore",
|
|
"mms",
|
|
"stable diffusion",
|
|
"instruction-following",
|
|
"sillytavern",
|
|
"layoutlmv3",
|
|
"tensorflow",
|
|
"storywriting",
|
|
"Llama3",
|
|
"science fiction",
|
|
"yolo",
|
|
"korean",
|
|
"pixel",
|
|
"speech-recognition",
|
|
"sv-SE",
|
|
"zh-CN",
|
|
"sdxl",
|
|
"sentiment analysis",
|
|
"biomedical",
|
|
"python",
|
|
"FrozenLake-v1-4x4",
|
|
"all genres",
|
|
"lm",
|
|
"russian",
|
|
"concept",
|
|
"text classification",
|
|
"flux-diffusers",
|
|
"dataset",
|
|
"granite",
|
|
"forecasting",
|
|
"roboflow",
|
|
"esc",
|
|
"romance",
|
|
"vivid writing",
|
|
"Math",
|
|
"falcon3",
|
|
"turkish",
|
|
"french",
|
|
"fairseq",
|
|
"Conformer",
|
|
"question answering",
|
|
"mllama",
|
|
"vivid prosing",
|
|
"generation",
|
|
"clinical",
|
|
"persian",
|
|
"esb",
|
|
"diffusion",
|
|
"time-series",
|
|
"sklearn",
|
|
"English",
|
|
"frankenmoe",
|
|
"model_stock",
|
|
"layoutlm",
|
|
"voice",
|
|
"whisper-event",
|
|
"mobilebert",
|
|
"paligemma",
|
|
"remote-sensing",
|
|
"function-calling",
|
|
"int8",
|
|
"QA",
|
|
"code-generation",
|
|
"MountainCar-v0",
|
|
"roboflow2huggingface",
|
|
"Flux",
|
|
"glm",
|
|
"computer vision",
|
|
"machine-translation",
|
|
"mathematics",
|
|
"DPO",
|
|
"simpletuner",
|
|
"gliner",
|
|
"sentence_embedding",
|
|
"german",
|
|
"fine-tuning",
|
|
"long-form-generation",
|
|
"exaone",
|
|
"lg-ai",
|
|
"deberta-v3",
|
|
"healthcare",
|
|
"nft",
|
|
"longt5",
|
|
"instruction",
|
|
"ai-toolkit",
|
|
"Stable Diffusion",
|
|
"time series",
|
|
"convbert",
|
|
"farsi",
|
|
"security",
|
|
"huggingnft",
|
|
"safety",
|
|
"long context",
|
|
"Quality Estimation",
|
|
"detr",
|
|
"stable-diffusion-api",
|
|
"phi",
|
|
"role-play",
|
|
"beit",
|
|
"regnet",
|
|
"named entity recognition",
|
|
"retrieval",
|
|
"Llama-3",
|
|
"ctranslate2",
|
|
"foundation models",
|
|
"fasttext",
|
|
"computer-vision",
|
|
"politics",
|
|
"segmentation",
|
|
"lycoris",
|
|
"health",
|
|
"woman",
|
|
"cohere",
|
|
"ultralytics",
|
|
"style-transfer",
|
|
"pretrained",
|
|
"speecht5",
|
|
"cybersecurity",
|
|
"RAG",
|
|
"asteroid",
|
|
"Instruct",
|
|
"internlm2",
|
|
"multiclass_classification",
|
|
"thudm",
|
|
"exaone-3.5",
|
|
"json mode",
|
|
"pretrained models",
|
|
"summary",
|
|
"girls",
|
|
"finnish",
|
|
"large language model",
|
|
"reward model",
|
|
"Text Classification",
|
|
"Long Context",
|
|
"celebrity",
|
|
"voxpopuli-v2",
|
|
"french law",
|
|
"droit fran\u00e7ais",
|
|
"modernbert",
|
|
"Llama",
|
|
"BERT",
|
|
"portuguese-speech-corpus",
|
|
"luke",
|
|
"multiberts-seed_0",
|
|
"multiberts-seed_1",
|
|
"multiberts-seed_2",
|
|
"multiberts-seed_3",
|
|
"multiberts-seed_4",
|
|
"Abstractive Summarization",
|
|
"CarRacing-v0",
|
|
"fp8",
|
|
"instruction-tuning",
|
|
"time series foundation models",
|
|
"multiberts-seed-0",
|
|
"speech-translation",
|
|
"chatbot",
|
|
"codegen",
|
|
"NSFW",
|
|
"multiberts-seed-1",
|
|
"multiberts-seed-2",
|
|
"multiberts-seed-3",
|
|
"multiberts-seed-4",
|
|
"siglip",
|
|
"LoRA",
|
|
"3D",
|
|
"reddit",
|
|
"Athene",
|
|
"Attention",
|
|
"SFT",
|
|
"pruna-ai",
|
|
"splinter",
|
|
"gary109/AI_Light_Dance",
|
|
"granite-3.1",
|
|
"CoT",
|
|
"yolov8",
|
|
"android",
|
|
"granite-3.0",
|
|
"Nexusflow",
|
|
"Qwen2.5",
|
|
"speech_to_text",
|
|
"language-model",
|
|
"pt-br",
|
|
"Transducer",
|
|
"artistic",
|
|
"historical",
|
|
"llamafile",
|
|
"Mistral",
|
|
"torchdistill",
|
|
"earth-observation",
|
|
"croissant",
|
|
"Chinese",
|
|
"esm",
|
|
"education",
|
|
"ChatGPT",
|
|
"reflection",
|
|
"zle",
|
|
"FrozenLake-v1-8x8",
|
|
"Pong-PLE-v0",
|
|
"any-to-any",
|
|
"ollama",
|
|
"Ollama",
|
|
"NLU",
|
|
"zero-shot",
|
|
"transformer",
|
|
"paraphrasing",
|
|
"fnet",
|
|
"Arabic",
|
|
"agriculture",
|
|
"catalan",
|
|
"information retrieval",
|
|
"alignment",
|
|
"preference",
|
|
"economics",
|
|
"optimum_habana",
|
|
"game",
|
|
"12b",
|
|
"funnel",
|
|
"whispering",
|
|
"infinite-dataset-hub",
|
|
"jw",
|
|
"deepseek_v2",
|
|
"speaker-diarization",
|
|
"olmo",
|
|
"protein",
|
|
"xglm",
|
|
"punctuation",
|
|
"rvc",
|
|
"linktransformer",
|
|
"fantasy",
|
|
"tweets",
|
|
"newspaper",
|
|
"conversation",
|
|
"Visual novel",
|
|
"BipedalWalker-v3",
|
|
"FrozenLake-v1-8x8-no_slippery",
|
|
"7b",
|
|
"blenderbot",
|
|
"pyannote-audio",
|
|
"pyannote",
|
|
"megatron-bert",
|
|
"gpt_bigcode",
|
|
"molecules",
|
|
"research",
|
|
"hybrid-clip",
|
|
"sil-ai/bloom-speech",
|
|
"danish",
|
|
"information-retrieval",
|
|
"food",
|
|
"engineering",
|
|
"ctrl",
|
|
"Intel\u00ae Neural Compressor",
|
|
"Text-to-Image",
|
|
"super-resolution",
|
|
"classical chinese",
|
|
"literary chinese",
|
|
"ancient chinese",
|
|
"emotion-classification",
|
|
"canine",
|
|
"tagalog",
|
|
"filipino",
|
|
"abstractive summarization",
|
|
"portuguese",
|
|
"text-to-sql",
|
|
"architecture",
|
|
"solar",
|
|
"torch",
|
|
"Not-for-all-Audiences",
|
|
"Reasoning",
|
|
"ultralyticsplus",
|
|
"llama.cpp",
|
|
"trocr",
|
|
"cross-encoder",
|
|
"passage-retrieval",
|
|
"insurance",
|
|
"vietnamese",
|
|
"Anime",
|
|
"crypto",
|
|
"fine-tuned",
|
|
"toxicity",
|
|
"fsmt",
|
|
"htr",
|
|
"ASR",
|
|
"baichuan",
|
|
"cute",
|
|
"machine learning",
|
|
"roformer",
|
|
"Roleplay",
|
|
"history",
|
|
"national library of spain",
|
|
"satellite-imagery",
|
|
"structure-prediction",
|
|
"data-juicer",
|
|
"Pytorch",
|
|
"speaker",
|
|
"Sentence Transformers",
|
|
"OCR",
|
|
"VLM",
|
|
"embedding",
|
|
"character",
|
|
"norwegian",
|
|
"paraphrase",
|
|
"MSA",
|
|
"language model",
|
|
"xlm",
|
|
"grammar",
|
|
"reranking",
|
|
"endpoints-template",
|
|
"dreambooth",
|
|
"literature",
|
|
"sdxl-sliders",
|
|
"ntcai.xyz-sliders",
|
|
"FelixChao/WestSeverus-7B-DPO-v2",
|
|
"prompts",
|
|
"sample-factory",
|
|
"bioinformatics",
|
|
"Mr Porter",
|
|
"Diffusers",
|
|
"Code",
|
|
"financial",
|
|
"tool-use",
|
|
"v8",
|
|
"stablediffusionapi.com",
|
|
"realism",
|
|
"Chat Model",
|
|
"perceiver",
|
|
"RoBERTa",
|
|
"reviews",
|
|
"zhs",
|
|
"knowledge-distillation",
|
|
"paddlepaddle",
|
|
"deutsch",
|
|
"hate speech",
|
|
"business",
|
|
"monotransquest",
|
|
"sew-d",
|
|
"corenlp",
|
|
"speechmix",
|
|
"data-to-text",
|
|
"phi3_v",
|
|
"vidore",
|
|
"falcon",
|
|
"keypoint-detection",
|
|
"Safetensors",
|
|
"Text Generation",
|
|
"8b",
|
|
"relation-extraction",
|
|
"indicnlp",
|
|
"mT5",
|
|
"image-super-resolution",
|
|
"speech-to-speech-translation",
|
|
"gpt3",
|
|
"genomics",
|
|
"decision_transformer",
|
|
"swinv2",
|
|
"xclip",
|
|
"aiart",
|
|
"handwritten",
|
|
"arabic",
|
|
"ggml",
|
|
"styles",
|
|
"text adventure",
|
|
"web",
|
|
"Biology",
|
|
"glove",
|
|
"experimental",
|
|
"hate-speech",
|
|
"ConvTasNet",
|
|
"fnet-bert-base-comparison",
|
|
"ilgiornale",
|
|
"repubblica",
|
|
"psychology",
|
|
"Net",
|
|
"parler_tts",
|
|
"annotation",
|
|
"video-generation",
|
|
"colpali",
|
|
"dino",
|
|
"llava_next",
|
|
"maskformer",
|
|
"sagemaker",
|
|
"tensorflowtts",
|
|
"natural-language-understanding",
|
|
"LLaMA",
|
|
"astronomy",
|
|
"atr",
|
|
"stablelm",
|
|
"poetry",
|
|
"4bit",
|
|
"vlm",
|
|
"Art",
|
|
"agent",
|
|
"vqa",
|
|
"fse",
|
|
"Walker2DBulletEnv-v0",
|
|
"text-mining",
|
|
"3b",
|
|
"financial-sentiment-analysis",
|
|
"minicpmv",
|
|
"relation extraction",
|
|
"bitnet",
|
|
"social media",
|
|
"yolos",
|
|
"dinov2",
|
|
"donut",
|
|
"mamba",
|
|
"photo",
|
|
"chocolatine",
|
|
"books",
|
|
"Spanish",
|
|
"protein language model",
|
|
"super-image",
|
|
"data2vec-audio",
|
|
"cyber security",
|
|
"deberta-mnli",
|
|
"ernie",
|
|
"text-embedding",
|
|
"midjourney",
|
|
"ai",
|
|
"7B",
|
|
"bardsai/jaskier-7b-dpo-v5.6",
|
|
"skops",
|
|
"open-source",
|
|
"token classification",
|
|
"green",
|
|
"valiant",
|
|
"valiant-labs",
|
|
"illustrious",
|
|
"coding",
|
|
"sd3.5-large",
|
|
"stance-detection",
|
|
"thai",
|
|
"gensim",
|
|
"SEAD",
|
|
"trajectory_transformer",
|
|
"word-segmentation",
|
|
"diffusion-single-file",
|
|
"mixture of experts",
|
|
"legal liability",
|
|
"convAI",
|
|
"vision-language",
|
|
"rwkv",
|
|
"Multimodal",
|
|
"depth",
|
|
"modelslab.com",
|
|
"sd3",
|
|
"Dutch",
|
|
"Sentence Similarity",
|
|
"document-expansion",
|
|
"uncased",
|
|
"Riva",
|
|
"chatgpt",
|
|
"Composer",
|
|
"MosaicML",
|
|
"llm-foundry",
|
|
"ai-safety",
|
|
"qlora",
|
|
"Decoder",
|
|
"AI",
|
|
"deepseek",
|
|
"environment",
|
|
"imagepipeline",
|
|
"imagepipeline.io",
|
|
"SQL",
|
|
"base",
|
|
"Logic",
|
|
"technical",
|
|
"chess",
|
|
"Chemistry",
|
|
"satellite",
|
|
"next-sentence-prediction",
|
|
"allennlp",
|
|
"PostTrainingStatic",
|
|
"dk",
|
|
"HalfCheetahBulletEnv-v0",
|
|
"medicine",
|
|
"synthetic-dataset",
|
|
"Physics",
|
|
"lrgb",
|
|
"ControlNet",
|
|
"e-commerce",
|
|
"stocks",
|
|
"information extraction",
|
|
"encoder",
|
|
"T5",
|
|
"nomic_bert",
|
|
"Summarization",
|
|
"LLMs",
|
|
"drug-discovery",
|
|
"CLIP",
|
|
"summarisation",
|
|
"semantic role labeling",
|
|
"tapex",
|
|
"NLI",
|
|
"Russian",
|
|
"audio-source-separation",
|
|
"generative",
|
|
"scifi",
|
|
"RLAIF",
|
|
"pathology",
|
|
"Python",
|
|
"chain-of-thought",
|
|
"programming",
|
|
"llama-3.2",
|
|
"llama-3-instruct",
|
|
"computer-science",
|
|
"gguf-my-lora",
|
|
"Arknights",
|
|
"\u660e\u65e5\u65b9\u821f",
|
|
"timelms",
|
|
"resnetd",
|
|
"neural-compressor",
|
|
"paraphrase-identification",
|
|
"wiki",
|
|
"sentinel-2",
|
|
"image-text-dataset",
|
|
"training",
|
|
"musicgen",
|
|
"background-removal",
|
|
"roa",
|
|
"custom-research",
|
|
"8B",
|
|
"logic",
|
|
"argumentation",
|
|
"nllb",
|
|
"movie",
|
|
"Turkish",
|
|
"2D",
|
|
"Language",
|
|
"TDNN",
|
|
"people",
|
|
"SmallMoleculeMultiView",
|
|
"binding-affinity-prediction",
|
|
"bio-medical",
|
|
"drug-target-interaction",
|
|
"molecular-property-prediction",
|
|
"moleculenet",
|
|
"multi-view",
|
|
"small-molecules",
|
|
"virtual-screening",
|
|
"text2sql",
|
|
"search",
|
|
"Arabic Text Summarization",
|
|
"indobenchmark",
|
|
"object detection",
|
|
"question",
|
|
"booksum",
|
|
"long-document",
|
|
"SepFormer",
|
|
"squeezebert",
|
|
"bag-of-words",
|
|
"TTS",
|
|
"mobilevit",
|
|
"Question Answering",
|
|
"beir",
|
|
"furry",
|
|
"privacy",
|
|
"FastConformer",
|
|
"sail-rvc",
|
|
"unity-sentis",
|
|
"preferences",
|
|
"int4",
|
|
"UnfilteredAI",
|
|
"sd3-diffusers",
|
|
"spectrum",
|
|
"recommendation",
|
|
"youtube",
|
|
"compsci",
|
|
"Llama-cpp",
|
|
"MountainCarContinuous-v0",
|
|
"3B",
|
|
"knowledge-graph",
|
|
"k2",
|
|
"tf2.0",
|
|
"icelandic",
|
|
"codemix",
|
|
"ukrainian",
|
|
"text-classfication",
|
|
"ML-Agents-Worm",
|
|
"pythae",
|
|
"reproducibility",
|
|
"fine-tune",
|
|
"Dataset",
|
|
"Culture",
|
|
"LeRobot",
|
|
"blip-2",
|
|
"idefics3",
|
|
"inc",
|
|
"general-purpose",
|
|
"cogvideox",
|
|
"cancer",
|
|
"fluently-lm",
|
|
"thinking",
|
|
"Identification",
|
|
"commercial use",
|
|
"code generation",
|
|
"flux-dev",
|
|
"HelpingAI",
|
|
"Code Generation",
|
|
"Czech",
|
|
"bigbird_pegasus",
|
|
"detection",
|
|
"dcgan",
|
|
"decision-transformer",
|
|
"gym-continous-control",
|
|
"CaText",
|
|
"Catalan Textual Corpus",
|
|
"videomae",
|
|
"Multilingual",
|
|
"text-clustering",
|
|
"text-semantic-similarity",
|
|
"text-evaluation",
|
|
"text-reranking",
|
|
"awesome-yolov8-models",
|
|
"language-identification",
|
|
"controlnet-v1-1",
|
|
"photography",
|
|
"self-instruct",
|
|
"speech-to-text",
|
|
"animals",
|
|
"jais",
|
|
"Information Extraction",
|
|
"philosophy",
|
|
"illustration",
|
|
"mlc-llm",
|
|
"nemotron",
|
|
"2.5D",
|
|
"extreme swearing",
|
|
"mistral nemo",
|
|
"design",
|
|
"shining-valiant",
|
|
"AstralFusion",
|
|
"TIES",
|
|
"Pendulum-v1",
|
|
"indie",
|
|
"xlm-roberta-large",
|
|
"formality-style-transfer",
|
|
"textual-entailment",
|
|
"movies",
|
|
"visual_bert",
|
|
"lexical normalization",
|
|
"email",
|
|
"bygpt5",
|
|
"datacraft",
|
|
"medium",
|
|
"language modelling",
|
|
"multi-modal-qa",
|
|
"math-qa",
|
|
"language-agent",
|
|
"long-context",
|
|
"tokenization",
|
|
"zh-tw",
|
|
"overlapped-speech-detection",
|
|
"arctic",
|
|
"speaker-segmentation",
|
|
"Vision",
|
|
"Text",
|
|
"ColBERT",
|
|
"prompt",
|
|
"idefics2",
|
|
"ONNX",
|
|
"sapiens",
|
|
"MLLM",
|
|
"aimv2",
|
|
"big_vision",
|
|
"Llama-Cpp",
|
|
"MIDI",
|
|
"vilt",
|
|
"bert-base",
|
|
"reformer",
|
|
"speech-emotion-recognition",
|
|
"deberta-v1",
|
|
"Flemish",
|
|
"RobBERT",
|
|
"long-form",
|
|
"text-to-mel",
|
|
"semantic-search",
|
|
"keyphrase-extraction",
|
|
"spelling",
|
|
"setfit",
|
|
"paraphrase-generation",
|
|
"aiartchan",
|
|
"LLaVA",
|
|
"internlm",
|
|
"astrophysics",
|
|
"h2o-llmstudio",
|
|
"blockchain",
|
|
"xl",
|
|
"IE",
|
|
"jailbreak",
|
|
"Portuguese",
|
|
"Q&A",
|
|
"langchain",
|
|
"scenery",
|
|
"city",
|
|
"phishing",
|
|
"clip_vision_model",
|
|
"web-llm",
|
|
"8bit",
|
|
"WizardLM/WizardMath-7B-V1.1",
|
|
"Mixtral",
|
|
"fusechat",
|
|
"binary",
|
|
"bggpt",
|
|
"insait",
|
|
"efficient",
|
|
"chameleon",
|
|
"16-bit",
|
|
"quantization",
|
|
"lifescience",
|
|
"social",
|
|
"bangla",
|
|
"Embodied AI",
|
|
"shining-valiant-2",
|
|
"ANDSystem",
|
|
"bengali",
|
|
"sparsh",
|
|
"DarkStock",
|
|
"Aspire",
|
|
"Storm",
|
|
"DarkEnigma",
|
|
"vicgalle/Configurable-Hermes-2-Pro-Llama-3-8B",
|
|
"conversational-ai",
|
|
"graphic horror",
|
|
"novel",
|
|
"transfo-xl",
|
|
"nystromformer",
|
|
"answer extraction",
|
|
"commonsense-reasoning",
|
|
"newspapers",
|
|
"GPT-4",
|
|
"chart",
|
|
"common crawl",
|
|
"Gucci",
|
|
"gguf-comfy",
|
|
"pyannote-audio-pipeline",
|
|
"ud",
|
|
"mbart-50",
|
|
"pyannote-audio-model",
|
|
"Chat",
|
|
"entity recognition",
|
|
"Sentiment",
|
|
"Architecture",
|
|
"DML",
|
|
"ONNXRuntime",
|
|
"SDXL",
|
|
"ethics",
|
|
"Agent",
|
|
"rubert",
|
|
"multiclass",
|
|
"tiny",
|
|
"xls_r",
|
|
"keytotext",
|
|
"indobert",
|
|
"Source Separation",
|
|
"Speech Separation",
|
|
"sequence-classification",
|
|
"baseline-trainer",
|
|
"text2image",
|
|
"mask2former",
|
|
"yolov5",
|
|
"Named Entity Recognition",
|
|
"DNA",
|
|
"sam",
|
|
"deep-learning",
|
|
"CV",
|
|
"moderation",
|
|
"midi",
|
|
"tax",
|
|
"Event Extraction",
|
|
"Relation Extraction",
|
|
"wav2vec2-bert",
|
|
"model-fusion",
|
|
"automerger",
|
|
"hindi",
|
|
"materials science",
|
|
"enhanced",
|
|
"retrieval-augmented-generation",
|
|
"SMILES",
|
|
"regression",
|
|
"medical imaging",
|
|
"jais-family",
|
|
"RP",
|
|
"book",
|
|
"o1",
|
|
"sexy",
|
|
"COCO",
|
|
"mlx-my-repo",
|
|
"swedish",
|
|
"COT",
|
|
"adaption",
|
|
"recycled",
|
|
"DA",
|
|
"commonsense",
|
|
"icefall",
|
|
"data2vec-text",
|
|
"headline-generation",
|
|
"codeswitching",
|
|
"natural language understanding",
|
|
"social-media",
|
|
"wav2vec2-conformer",
|
|
"fact checking",
|
|
"QbertNoFrameskip-v4",
|
|
"ddpm_diffusion",
|
|
"tweet",
|
|
"ANDDigest",
|
|
"conversations-summarization",
|
|
"verification",
|
|
"PDF",
|
|
"LM",
|
|
"hate speech detection",
|
|
"wikidata",
|
|
"bio-chem",
|
|
"molnet",
|
|
"molecule-net",
|
|
"biophysics",
|
|
"godot-rl",
|
|
"environments",
|
|
"video-games",
|
|
"regularization-images",
|
|
"class-instance",
|
|
"preservation-loss-training",
|
|
"protein structure",
|
|
"spacerunner",
|
|
"blip",
|
|
"moondream1",
|
|
"multi_modality",
|
|
"Taiwan",
|
|
"pdf",
|
|
"speaker-change-detection",
|
|
"idol",
|
|
"inpainting",
|
|
"Inference Endpoints",
|
|
"Medical",
|
|
"MiniCPM",
|
|
"vla",
|
|
"reranker",
|
|
"Photography",
|
|
"splade",
|
|
"SPO",
|
|
"model2vec",
|
|
"chatqa",
|
|
"QwQ",
|
|
"sana",
|
|
"Sana",
|
|
"GPT-2",
|
|
"music-generation",
|
|
"xlm-roberta-xl",
|
|
"Keywords to Sentences",
|
|
"aspect-based-sentiment-analysis",
|
|
"radiology",
|
|
"GAN",
|
|
"image-text",
|
|
"mobilenet_v2",
|
|
"dreambooth-hackathon",
|
|
"painting",
|
|
"pix2struct",
|
|
"face",
|
|
"labse",
|
|
"histology",
|
|
"flan",
|
|
"Named Entity Recogniton",
|
|
"mistral-7b",
|
|
"lmm",
|
|
"Alpaca",
|
|
"gpt2-medium",
|
|
"orca",
|
|
"buildings",
|
|
"cartoon",
|
|
"augmentation",
|
|
"espa\u00f1ol",
|
|
"cyber",
|
|
"CultriX/Wernicke-7B-v9",
|
|
"Audio",
|
|
"VQA",
|
|
"liminerity/merge",
|
|
"gemma_torch",
|
|
"keras-hub",
|
|
"on-device language model",
|
|
"trained",
|
|
"instructions",
|
|
"materials",
|
|
"openelm",
|
|
"lab",
|
|
"heathcare",
|
|
"Pharmaceutical",
|
|
"Pharma",
|
|
"llama-3-ko",
|
|
"Science",
|
|
"parallel",
|
|
"multi-turn",
|
|
"ov",
|
|
"LLM Agent",
|
|
"gptqmodel",
|
|
"modelcloud",
|
|
"transliteration",
|
|
"autoquant",
|
|
"image classification",
|
|
"llava_onevision",
|
|
"auto-gptq",
|
|
"safe-for-work",
|
|
"moshi",
|
|
"128k context",
|
|
"theprint",
|
|
"multiturn",
|
|
"llama-3.1-instruct",
|
|
"tactile",
|
|
"technical-assistance",
|
|
"structured-output",
|
|
"Llama3.2",
|
|
"natural-language-processing",
|
|
"vision-text-dual-encoder",
|
|
"lxmert",
|
|
"realm",
|
|
"machine translation",
|
|
"prophetnet",
|
|
"cnlpt",
|
|
"pos-tagging",
|
|
"kd",
|
|
"sparql",
|
|
"BipedalWalkerHardcore-v3",
|
|
"BreakoutNoFrameskip-v4",
|
|
"BeamRiderNoFrameskip-v4",
|
|
"dutch",
|
|
"math-word-problems",
|
|
"grounding",
|
|
"safe",
|
|
"Benchmark",
|
|
"example",
|
|
"touch rugby",
|
|
"self-supervised-pretraining",
|
|
"dual_ar",
|
|
"Flux.1-Dev",
|
|
"background",
|
|
"sound language model",
|
|
"chain_of_thought",
|
|
"stock market",
|
|
"ROC",
|
|
"multi-image",
|
|
"molmo",
|
|
"immich",
|
|
"hunyuan",
|
|
"machine tranlsation",
|
|
"O1-like model",
|
|
"saelens",
|
|
"Realism",
|
|
"bitcoin",
|
|
"pythia",
|
|
"starcoder2",
|
|
"open",
|
|
"stablelm_epoch",
|
|
"granitemoe",
|
|
"tulu",
|
|
"Italian",
|
|
"gender",
|
|
"toxic comments classification",
|
|
"Arabic T5",
|
|
"k2t",
|
|
"GPT",
|
|
"spam",
|
|
"dpt",
|
|
"punctuation prediction",
|
|
"pre-training",
|
|
"pysentimiento",
|
|
"speech-enhancement",
|
|
"Audio Source Separation",
|
|
"ranking",
|
|
"tc",
|
|
"query-expansion",
|
|
"Finance",
|
|
"named-entity-linking",
|
|
"Citrinet",
|
|
"retrieval augmented generation",
|
|
"core-ml",
|
|
"Tensorflow",
|
|
"Vietnamese",
|
|
"analysis",
|
|
"quant",
|
|
"vicuna",
|
|
"dialogue-summarization",
|
|
"Cybersecurity",
|
|
"t5-small",
|
|
"shot",
|
|
"zxx",
|
|
"prk",
|
|
"tag2",
|
|
"slerp",
|
|
"q4_k_m",
|
|
"q8_0",
|
|
"bias",
|
|
"remote sensing",
|
|
"openchat",
|
|
"deep learning",
|
|
"t5x",
|
|
"computer science",
|
|
"review",
|
|
"seedbox",
|
|
"Maths",
|
|
"natural language processing",
|
|
"remyx",
|
|
"farming",
|
|
"Equall/Saul-Base",
|
|
"brazil",
|
|
"knowledge",
|
|
"instruction tuning",
|
|
"AWQ",
|
|
"Enterprise LLM",
|
|
"Enterprise",
|
|
"Enterprise ready",
|
|
"multimodal large language model",
|
|
"Qwen2",
|
|
"machine-learning",
|
|
"Llama3.1",
|
|
"generative-ai",
|
|
"monet",
|
|
"fast-apply",
|
|
"instant-apply",
|
|
"TIES_merge",
|
|
"TheSpice",
|
|
"Yggdrasil",
|
|
"Bluuwhale",
|
|
"magical-realism",
|
|
"sd3.5",
|
|
"sd3.5-diffusers",
|
|
"decisions",
|
|
"TLA",
|
|
"pegasus_x",
|
|
"F16",
|
|
"sailor",
|
|
"Translation",
|
|
"casual-lm",
|
|
"deit",
|
|
"microtransquest",
|
|
"hter",
|
|
"siamesetransquest",
|
|
"diarization",
|
|
"allenai",
|
|
"testing",
|
|
"xlm-prophetnet",
|
|
"entailment",
|
|
"qarib",
|
|
"minds14",
|
|
"projected-gan",
|
|
"rita",
|
|
"coptic",
|
|
"opt_metasq",
|
|
"HopperBulletEnv-v0",
|
|
"LunarLanderContinuous-v2",
|
|
"ML-Agents-PushBlock",
|
|
"spectrograms",
|
|
"mlconsole",
|
|
"qa-nli",
|
|
"games",
|
|
"sports",
|
|
"table",
|
|
"government",
|
|
"figure-qa",
|
|
"geometry-diagram",
|
|
"scientific-figure",
|
|
"Imitation Learning",
|
|
"Farfetch",
|
|
"corpus",
|
|
"amazon",
|
|
"synthetic-captions",
|
|
"planning",
|
|
"reward",
|
|
"lichess",
|
|
"dialog-response-generation",
|
|
"github-stars",
|
|
"Prada",
|
|
"deepseek_v3",
|
|
"coqui",
|
|
"video-to-video",
|
|
"f5-tts",
|
|
"llama_for_causal_lm",
|
|
"GLiNER",
|
|
"brainstorm 40x",
|
|
"ECAPA-TDNN",
|
|
"Interior",
|
|
"Food",
|
|
"llava_mistral",
|
|
"falcon_mamba",
|
|
"sql",
|
|
"Function Calling",
|
|
"Extraction",
|
|
"intern_vit_6b",
|
|
"RVC",
|
|
"Arabic Dialect",
|
|
"Arabic Machine Translation",
|
|
"Arabic News Title and Question Generation",
|
|
"Arabic Paraphrasing and Transliteration",
|
|
"Arabic Code-Switched Translation",
|
|
"vit_mae",
|
|
"xls_r_translation",
|
|
"distilroberta",
|
|
"election2020",
|
|
"speaker-recognition",
|
|
"speaker-verification",
|
|
"emotion-recognition",
|
|
"gmq",
|
|
"speech-synthesis",
|
|
"HalfCheetah-v3",
|
|
"entity-linking",
|
|
"error-correction",
|
|
"CNN",
|
|
"span-marker",
|
|
"relation classification",
|
|
"txtai",
|
|
"intent",
|
|
"building",
|
|
"landscape",
|
|
"diffusion-models-class",
|
|
"checkpoint",
|
|
"Nijijourney",
|
|
"text2vec",
|
|
"dreamshaper",
|
|
"stablediffusion",
|
|
"keywords",
|
|
"openai",
|
|
"simplification",
|
|
"foundation model",
|
|
"histopathology",
|
|
"minecraft",
|
|
"Network Intrusion Detection",
|
|
"GPT2",
|
|
"absa",
|
|
"media",
|
|
"retail",
|
|
"solidity",
|
|
"transcription",
|
|
"mel",
|
|
"tks",
|
|
"tag1",
|
|
"Sentiment Analysis",
|
|
"q2_k",
|
|
"q3_k_m",
|
|
"q5_k_m",
|
|
"q6_k",
|
|
"text-to-music",
|
|
"female",
|
|
"UNA",
|
|
"generated_from_setfit_trainer",
|
|
"scientific AI",
|
|
"polish",
|
|
"hacking",
|
|
"topic",
|
|
"depth_anything",
|
|
"ModelBest",
|
|
"THUNLP",
|
|
"yolov10",
|
|
"tracking",
|
|
"function",
|
|
"gaming",
|
|
"VILA",
|
|
"decompile",
|
|
"CorticalStack/pastiche-crown-clown-7b-dare-dpo",
|
|
"leaderboard",
|
|
"Law",
|
|
"labrador",
|
|
"VoxCeleb",
|
|
"static",
|
|
"zhtw",
|
|
"16bit",
|
|
"llava_qwen",
|
|
"java",
|
|
"autoawq",
|
|
"olmoe",
|
|
"nncf",
|
|
"Computer Vision",
|
|
"llmware-chat",
|
|
"cosmology",
|
|
"droit",
|
|
"role play",
|
|
"mobile",
|
|
"llama-3.1-instruct-8b",
|
|
"llama-3-instruct-8b",
|
|
"paper",
|
|
"actress",
|
|
"Video",
|
|
"mobilellm",
|
|
"Q4",
|
|
"Q5",
|
|
"Q8",
|
|
"AutoRound",
|
|
"indonesian",
|
|
"maths",
|
|
"synthetic-data",
|
|
"Earth Observation",
|
|
"accounting",
|
|
"stock",
|
|
"llama-ti",
|
|
"fluently-merge",
|
|
"Mathematics",
|
|
"NuSLERP",
|
|
"India",
|
|
"hentai",
|
|
"zlw",
|
|
"metric",
|
|
"audacity",
|
|
"pretrain",
|
|
"miniLM",
|
|
"spoken language understanding",
|
|
"cvt",
|
|
"keyphrase-generation",
|
|
"multi-displinary",
|
|
"levit",
|
|
"Walker2d-v3",
|
|
"Swimmer-v3",
|
|
"Hopper-v3",
|
|
"ReacherBulletEnv-v0",
|
|
"Ant-v3",
|
|
"MedicalNet",
|
|
"medical images",
|
|
"Med3D",
|
|
"clustering",
|
|
"email generation",
|
|
"tau/sled",
|
|
"afro-digits-speech",
|
|
"geography",
|
|
"research papers",
|
|
"explanation",
|
|
"graphic design",
|
|
"linguistics",
|
|
"instruct-tune",
|
|
"fairness",
|
|
"visual-reasoning",
|
|
"energy",
|
|
"NeRF",
|
|
"3D Vision",
|
|
"GPT-4V",
|
|
"Image",
|
|
"biology`",
|
|
"Burberry",
|
|
"video generation",
|
|
"Deepsync",
|
|
"image generation",
|
|
"candlesticks",
|
|
"option trading",
|
|
"captioning",
|
|
"minicpm-v",
|
|
"snowflake-arctic-embed",
|
|
"animatediff",
|
|
"sam2",
|
|
"Design",
|
|
"aria",
|
|
"emotions",
|
|
"ultravox",
|
|
"Midjourney",
|
|
"fluently-sets",
|
|
"Cinematic",
|
|
"Landscape",
|
|
"Car",
|
|
"Wildlife",
|
|
"jamba",
|
|
"audiocraft",
|
|
"static-embeddings",
|
|
"vidore-experimental",
|
|
"gte",
|
|
"mesh-generation",
|
|
"chatqa-1.5",
|
|
"Llama3 MOE",
|
|
"autogenerated-modelcard",
|
|
"historic",
|
|
"BERTje",
|
|
"go-emotion",
|
|
"negation",
|
|
"flaubert-base",
|
|
"fanpage",
|
|
"ilpost",
|
|
"anomaly detection",
|
|
"audio-frame-classification",
|
|
"pokemon",
|
|
"deformable_detr",
|
|
"byt5",
|
|
"WHAM!",
|
|
"enformer",
|
|
"Arabic News Title Generation",
|
|
"Arabic Paraphrasing",
|
|
"named-entity-disambiguation",
|
|
"entity-disambiguation",
|
|
"markuplm",
|
|
"Token Classification",
|
|
"grammar synthesis",
|
|
"invoices",
|
|
"conditional_detr",
|
|
"timesformer",
|
|
"cyberpunk",
|
|
"urdu",
|
|
"Automatic Speech Recognition",
|
|
"colbert",
|
|
"hate",
|
|
"offensive language",
|
|
"efficientnet",
|
|
"semantic search",
|
|
"text-image",
|
|
"sentence-embedding",
|
|
"g2p",
|
|
"characters",
|
|
"kandinsky",
|
|
"bertopic",
|
|
"KoAlpaca",
|
|
"safe-rlhf",
|
|
"girl",
|
|
"Classification",
|
|
"natural language generation",
|
|
"japanese-stablelm",
|
|
"mgpt",
|
|
"monai",
|
|
"foundation",
|
|
"infosec",
|
|
"cybersec",
|
|
"Instruction",
|
|
"optimum",
|
|
"prompt-injection",
|
|
"dolphin",
|
|
"stripedhyena",
|
|
"knowledge graph",
|
|
"phi-msft",
|
|
"information-extraction",
|
|
"phi-2",
|
|
"Yi",
|
|
"mlabonne/Marcoro14-7B-slerp",
|
|
"Image Classification",
|
|
"MoE",
|
|
"decruz07/kellemar-DPO-Orca-Distilled-7B-SLERP",
|
|
"vulnerability",
|
|
"GPT-SoVITS",
|
|
"controlnet model",
|
|
"turbo",
|
|
"reading comprehension",
|
|
"human feedback",
|
|
"aqlm",
|
|
"fluetnly-xl",
|
|
"fluently",
|
|
"AIGC",
|
|
"portugues",
|
|
"Rust",
|
|
"1bit",
|
|
"labradorite",
|
|
"interpretability",
|
|
"bilingual",
|
|
"biological materials",
|
|
"bioinspiration",
|
|
"steerlm",
|
|
"sarcasm",
|
|
"marketing",
|
|
"imat",
|
|
"GLiClass",
|
|
"small language models",
|
|
"large video-language model",
|
|
"relative depth",
|
|
"6bit",
|
|
"5bit",
|
|
"3bit",
|
|
"2bit",
|
|
"HelpSteer2",
|
|
"graph",
|
|
"p1",
|
|
"zamba2",
|
|
"StableDiffusion",
|
|
"legalkit",
|
|
"Machine Learning",
|
|
"manga",
|
|
"ML-Agents-Huggy",
|
|
"asian",
|
|
"tools",
|
|
"pixtral",
|
|
"llama 3.1",
|
|
"IBM",
|
|
"caption",
|
|
"code-instruct",
|
|
"Segmentation",
|
|
"gutenberg",
|
|
"Psychology",
|
|
"rewiz",
|
|
"doge",
|
|
"Coder",
|
|
"Small",
|
|
"edge",
|
|
"mochi-1-preview",
|
|
"bamba",
|
|
"Conversational",
|
|
"metamotivo",
|
|
"novel view synthesis",
|
|
"Autonomous Driving",
|
|
"textnet",
|
|
"porn",
|
|
"anthro",
|
|
"OpenCENIA",
|
|
"irish",
|
|
"Fill-Mask",
|
|
"gpt2-small",
|
|
"zls",
|
|
"deberta-v2`",
|
|
"rembert",
|
|
"mrc",
|
|
"authorship-identification",
|
|
"fire2020",
|
|
"pan2020",
|
|
"audio-xvector",
|
|
"dependency parsing",
|
|
"normalization",
|
|
"speech recognition",
|
|
"basque",
|
|
"sibyl",
|
|
"common-voice",
|
|
"TapasModel",
|
|
"text2text-question-answering",
|
|
"twitch",
|
|
"Electra",
|
|
"bertin",
|
|
"masked_bert",
|
|
"answer-extraction",
|
|
"mel-to-wav",
|
|
"News",
|
|
"yoso",
|
|
"speech_to_text_transformer",
|
|
"malaysia",
|
|
"SLU",
|
|
"understanding",
|
|
"AMRBART",
|
|
"mctct",
|
|
"FrozenLake-v1",
|
|
"mbart-cc25",
|
|
"seals/Walker2d-v0",
|
|
"Acrobot-v1",
|
|
"object-tracking",
|
|
"MaCoCu",
|
|
"doe2vec",
|
|
"exploratory-landscape-analysis",
|
|
"autoencoders",
|
|
"test",
|
|
"long-documents",
|
|
"coreference-nli",
|
|
"ratings",
|
|
"abstractive-summarization",
|
|
"ML",
|
|
"3D shapes",
|
|
"prompt engineering",
|
|
"Manufacturing",
|
|
"logical reasoning",
|
|
"OOD",
|
|
"language modeling",
|
|
"gpt-3.5",
|
|
"QnA",
|
|
"CodeSearchNet",
|
|
"fictitious dialogues",
|
|
"prototyping",
|
|
"custom-format",
|
|
"spirituality",
|
|
"geometry-reasoning",
|
|
"function-plot",
|
|
"Expert Trajectory",
|
|
"Louis Vuitton",
|
|
"land-cover-classification",
|
|
"change-detection",
|
|
"telecom",
|
|
"exams",
|
|
"multi-modal dialogue",
|
|
"dalle3",
|
|
"Natural Language Processing",
|
|
"clothing",
|
|
"dictionary",
|
|
"poem",
|
|
"metadata",
|
|
"large",
|
|
"speechbox_punc",
|
|
"keras-dreambooth",
|
|
"Logical-Reasoning",
|
|
"code-style",
|
|
"Saint Laurent",
|
|
"Loro Piana",
|
|
"Fendi",
|
|
"cohere2",
|
|
"Diffusion",
|
|
"Flux.1-dev",
|
|
"remove background",
|
|
"codepy",
|
|
"vae",
|
|
"bark",
|
|
"upscaler",
|
|
"SLM",
|
|
"video-understanding",
|
|
"voice-conversion",
|
|
"Healthcare & Lifesciences",
|
|
"BioMed",
|
|
"Salient Object Detection",
|
|
"olmo2",
|
|
"timesfm",
|
|
"demo",
|
|
"seamless_communication",
|
|
"in-the-wild",
|
|
"Intel",
|
|
"Qwen",
|
|
"llamacpp",
|
|
"photorealism",
|
|
"audio-generation",
|
|
"ovis",
|
|
"llava_phi",
|
|
"Quantization",
|
|
"flux.1",
|
|
"flux.1-dev",
|
|
"4x8B",
|
|
"baai-nova",
|
|
"math_lingo",
|
|
"openai-gpt",
|
|
"propaganda",
|
|
"codet5",
|
|
"xlm-r-distilroberta-base-paraphrase-v1",
|
|
"multilabel",
|
|
"distilgpt2",
|
|
"multi-speaker",
|
|
"KKY",
|
|
"FAV",
|
|
"cased",
|
|
"BART",
|
|
"autoencoder",
|
|
"emotion-detection",
|
|
"mental health",
|
|
"distilbart",
|
|
"vn",
|
|
"speaker-embedding",
|
|
"ancient",
|
|
"disease",
|
|
"dialog",
|
|
"Emotion",
|
|
"Speaker",
|
|
"Verification",
|
|
"stylegan",
|
|
"stylegan3",
|
|
"coreference resolution",
|
|
"entity-retrieval",
|
|
"pubmedbert",
|
|
"NLG",
|
|
"jukebox",
|
|
"self-supervised learning",
|
|
"lean_albert",
|
|
"sarcasm-detection",
|
|
"SentimentAnalysis",
|
|
"not-for-all-eyes",
|
|
"instruction fine-tuning",
|
|
"Arabic BERT",
|
|
"Masked Langauge Model",
|
|
"RefinedWebModel",
|
|
"table extraction",
|
|
"tokenizer",
|
|
"deepspeed",
|
|
"taxonomy",
|
|
"artwork",
|
|
"Network Packets",
|
|
"NxtWave-GenAI-Webinar",
|
|
"finetuner",
|
|
"text-to-code",
|
|
"wizard",
|
|
"tokenizers",
|
|
"wizardlm",
|
|
"midi_model",
|
|
"smart contract",
|
|
"animation",
|
|
"decoder",
|
|
"future stock prediction",
|
|
"trends prediction",
|
|
"nature",
|
|
"image recognition",
|
|
"opensource",
|
|
"microsoft",
|
|
"spellcheck",
|
|
"pixel art",
|
|
"earth science",
|
|
"vision-language model",
|
|
"RyzenAI",
|
|
"modern",
|
|
"flowers",
|
|
"proteins",
|
|
"bnb",
|
|
"australia",
|
|
"maywell/PiVoT-0.1-Starling-LM-RP",
|
|
"Personality",
|
|
"German",
|
|
"argilla/distilabeled-Marcoro14-7B-slerp",
|
|
"atari",
|
|
"TDT",
|
|
"IGN",
|
|
"Table",
|
|
"smiles",
|
|
"deep signal processing",
|
|
"hybrid",
|
|
"graph problem",
|
|
"tinyllava",
|
|
"cosmopedia",
|
|
"patent",
|
|
"PII",
|
|
"learned sparse",
|
|
"MaziyarPanahi/Calme-7B-Instruct-v0.1.1",
|
|
"similarity",
|
|
"llms",
|
|
"jeiku/Eros_Prodigadigm_7B",
|
|
"Misral",
|
|
"instruction-tuned",
|
|
"rkllm",
|
|
"emoji",
|
|
"large language models",
|
|
"phi-3",
|
|
"Chatbot",
|
|
"Graph",
|
|
"Java",
|
|
"Research",
|
|
"hunyuan-dit",
|
|
"wildfire",
|
|
"cogvlm2",
|
|
"flash",
|
|
"hinglish",
|
|
"32 bit upscale",
|
|
"mllm",
|
|
"openvla",
|
|
"AI safety",
|
|
"Education",
|
|
"EQ",
|
|
"mobilenet_v3",
|
|
"translate",
|
|
"Japanese",
|
|
"OpenHermes-2.5",
|
|
"Orca",
|
|
"SlimOrca",
|
|
"aimo",
|
|
"electronics",
|
|
"neural-vocoder",
|
|
"AI4Science",
|
|
"Any2Any",
|
|
"bash",
|
|
"diffusionkit",
|
|
"OpenAI",
|
|
"anthracite-org/magnum-12b-v2",
|
|
"Huggy",
|
|
"misinformation",
|
|
"GUI",
|
|
"nynorsk",
|
|
"tibetan",
|
|
"llama-3.2-instruct",
|
|
"llama-3.2-instruct-3b",
|
|
"llama-3-instruct-3b",
|
|
"openthaigpt",
|
|
"azure",
|
|
"pruned",
|
|
"small",
|
|
"moonshine",
|
|
"Theresa",
|
|
"\u7279\u857e\u897f\u5a05",
|
|
"\u9b54\u738b",
|
|
"context 128k",
|
|
"slm",
|
|
"img2img",
|
|
"shuttle",
|
|
"backyard",
|
|
"BharatGPT",
|
|
"CoRover",
|
|
"chatbots",
|
|
"frankenmerge",
|
|
"Reddit",
|
|
"Neumind",
|
|
"recipe",
|
|
"feedback",
|
|
"article",
|
|
"Long-CoT",
|
|
"RL",
|
|
"dinov2_with_registers",
|
|
"Keras",
|
|
"multi-label",
|
|
"program-synthesis",
|
|
"abusive language",
|
|
"bat",
|
|
"bert-base-uncased",
|
|
"Sinhala",
|
|
"t5-new-failed",
|
|
"t5-new-hf-not-loaded",
|
|
"transducer",
|
|
"ibert",
|
|
"blenderbot-small",
|
|
"clip-vision-bert",
|
|
"code_synthesis",
|
|
"t5-lm-adapt",
|
|
"opennmt",
|
|
"semantic-role-labeling",
|
|
"osanseviero/hubert_base",
|
|
"xlm-roberta-base",
|
|
"sentence classification",
|
|
"mbert",
|
|
"QARiB",
|
|
"poolformer",
|
|
"dense-passage-retrieval",
|
|
"questions",
|
|
"modularNMT",
|
|
"fake-news",
|
|
"data2vec-vision",
|
|
"PostTrainingDynamic",
|
|
"ofa",
|
|
"PongNoFrameskip-v4",
|
|
"EnduroNoFrameskip-v4",
|
|
"AsteroidsNoFrameskip-v4",
|
|
"omnivore",
|
|
"Financial Language Modelling",
|
|
"MRC",
|
|
"video-object-segmentation",
|
|
"contrastive learning",
|
|
"metric learning",
|
|
"MONAI",
|
|
"vit_msn",
|
|
"claim-detection",
|
|
"image segmentation",
|
|
"hierarchical-transformer",
|
|
"context-sql",
|
|
"sqlglot",
|
|
"sociology",
|
|
"grammatical-error-correction",
|
|
"text-editing",
|
|
"quran",
|
|
"noisy-speech-recognition",
|
|
"Construction",
|
|
"Logistics",
|
|
"Detection",
|
|
"Protein",
|
|
"3D scenes",
|
|
"Instruction Response",
|
|
"parliament",
|
|
"sentiment analysis, Twitter, tweets",
|
|
"captions",
|
|
"simulation",
|
|
"table-understanding",
|
|
"GPT-3.5",
|
|
"Claude",
|
|
"mask",
|
|
"geometry-qa",
|
|
"logical-reasoning",
|
|
"synthetic-scene",
|
|
"plot",
|
|
"puzzle-test",
|
|
"Compilation",
|
|
"electricity",
|
|
"maltese",
|
|
"3D Gaussian",
|
|
"Novel View Synthesis",
|
|
"Text to 3D",
|
|
"Image to 3D",
|
|
"Lilac",
|
|
"arXiv",
|
|
"problem solving",
|
|
"Preference",
|
|
"eval",
|
|
"photos",
|
|
"text data",
|
|
"jokes",
|
|
"world",
|
|
"russia",
|
|
"other-image-super-resolution",
|
|
"readability",
|
|
"multiword-expression-detection",
|
|
"coreference",
|
|
"geo",
|
|
"ciempiess",
|
|
"mexican spanish",
|
|
"ciempiess project",
|
|
"ciempiess-unam project",
|
|
"anthrope",
|
|
"Multi-Step-Deductive-Reasoning",
|
|
"spotlight",
|
|
"ghana",
|
|
"ltx-video",
|
|
"virtual try-on",
|
|
"creative-writer",
|
|
"multiplicative-lora",
|
|
"deep-think",
|
|
"qwen2_audio",
|
|
"world model",
|
|
"torchtune",
|
|
"stable-audio-tools",
|
|
"multi-class",
|
|
"apollo",
|
|
"pixmo",
|
|
"mdeberta",
|
|
"resegmentation",
|
|
"facial-recognition",
|
|
"sentiment extraction",
|
|
"Text2Text Generation",
|
|
"sentencepiece",
|
|
"audio-spectrogram-transformer",
|
|
"Dichotomous Image Segmentation",
|
|
"Camouflaged Object Detection",
|
|
"ethereum",
|
|
"table-transformer",
|
|
"multitask",
|
|
"tasksource",
|
|
"owlv2",
|
|
"monocular depth estimation",
|
|
"playground",
|
|
"automation",
|
|
"assistant",
|
|
"clickbait",
|
|
"llava-qwen2",
|
|
"codegeex",
|
|
"sound",
|
|
"FLUX.1-dev",
|
|
"LLM2CLIP",
|
|
"comfyui",
|
|
"Prompt_Enhance",
|
|
"Multi-language",
|
|
"mingru",
|
|
"piano",
|
|
"fluxpipeline",
|
|
"genre",
|
|
"xlsr-fine-tuning",
|
|
"Biomedical",
|
|
"bluebert",
|
|
"bionlp",
|
|
"entity linking",
|
|
"fairlex",
|
|
"dallebart",
|
|
"historic german",
|
|
"phoneme-recognition",
|
|
"emotion-analysis",
|
|
"flue",
|
|
"indogpt",
|
|
"indonlg",
|
|
"tags",
|
|
"imagegpt",
|
|
"classical",
|
|
"chemical",
|
|
"rna",
|
|
"industry",
|
|
"sentence-bert",
|
|
"distilbart-mnli",
|
|
"dit",
|
|
"linkbert",
|
|
"biobart",
|
|
"javascript",
|
|
"Deepspeed",
|
|
"Megatron",
|
|
"job postings",
|
|
"ESG",
|
|
"bert-base-cased",
|
|
"biodiversity",
|
|
"Tacotron2",
|
|
"Vocoder",
|
|
"ddim_diffusion",
|
|
"nezha",
|
|
"denoising",
|
|
"patents",
|
|
"document encoder",
|
|
"loss",
|
|
"Tensor Flow",
|
|
"romanian",
|
|
"gpt-neo",
|
|
"protein embedding",
|
|
"chinese_clip",
|
|
"oneformer",
|
|
"STS",
|
|
"biogpt",
|
|
"prompt-generator",
|
|
"depression",
|
|
"prompt-retrieval",
|
|
"stable-diffusion-1.5",
|
|
"paddlenlp",
|
|
"geolocalization",
|
|
"urban",
|
|
"clap",
|
|
"Norwegian",
|
|
"vector search",
|
|
"gmp-dev",
|
|
"if",
|
|
"guanaco",
|
|
"generated_from_span_marker_trainer",
|
|
"laion",
|
|
"face-generation",
|
|
"StreamingDatasets",
|
|
"tfjs",
|
|
"word2vec",
|
|
"instructblip",
|
|
"float16",
|
|
"api",
|
|
"fish",
|
|
"table structure recognition",
|
|
"RefinedWeb",
|
|
"Text-to-Video",
|
|
"musicgen_melody",
|
|
"discord",
|
|
"voice model",
|
|
"species",
|
|
"rare species",
|
|
"endangered species",
|
|
"evolutionary biology",
|
|
"knowledge-guided",
|
|
"faster-whisper",
|
|
"latin",
|
|
"spellchecking",
|
|
"hezar",
|
|
"indonesia",
|
|
"captcha",
|
|
"openskyml",
|
|
"diffusion model",
|
|
"music generation",
|
|
"code llama",
|
|
"suicide",
|
|
"rpg",
|
|
"t2i-adapter",
|
|
"portrait",
|
|
"nougat",
|
|
"grounding-dino",
|
|
"sales",
|
|
"tinyllama",
|
|
"comedy",
|
|
"Llama 2",
|
|
"Hate Speech Detection",
|
|
"Mathematical Reasoning",
|
|
"mplug_owl2",
|
|
"hermes",
|
|
"hearthstone",
|
|
"funny",
|
|
"person",
|
|
"rwkv5",
|
|
"dalle-3",
|
|
"dalle",
|
|
"ultrafeedback",
|
|
"vibrant",
|
|
"comic",
|
|
"cinematic",
|
|
"drawing",
|
|
"space",
|
|
"injection",
|
|
"kurdish",
|
|
"LCM",
|
|
"juanako",
|
|
"video understanding",
|
|
"YOLO",
|
|
"C-RLFT",
|
|
"threat",
|
|
"MBTI",
|
|
"beowolx/CodeNinja-1.0-OpenChat-7B",
|
|
"TensorFlow",
|
|
"samir-fama/SamirGPT-v1",
|
|
"abacusai/Slerp-CM-mist-dpo",
|
|
"Large Language Models",
|
|
"Image-to-Text",
|
|
"recognition",
|
|
"uzbek",
|
|
"dvilasuero/DistilabelBeagle14-7B",
|
|
"MemGPT",
|
|
"YOLOv8",
|
|
"AiMavenAi/AiMaven-Prometheus",
|
|
"taiwan",
|
|
"\ud83e\udd68",
|
|
"laser",
|
|
"generative_ai",
|
|
"qwen2_moe",
|
|
"eren23/ogno-monarch-jaskier-merge-7b",
|
|
"mobileclip",
|
|
"opensearch",
|
|
"Equall/Saul-Instruct-v1",
|
|
"speech-to-speech",
|
|
"calme",
|
|
"Logical Reasoning",
|
|
"lightning",
|
|
"Undi95/LewdMistral-7B-0.2",
|
|
"brasil",
|
|
"freeze",
|
|
"svbrdf",
|
|
"arcee-ai/sec-mistral-7b-instruct-1.6-epoch",
|
|
"Cyber-Series",
|
|
"aesthetic",
|
|
"rockchip",
|
|
"rk3588",
|
|
"Legal",
|
|
"Ruby",
|
|
"allknowingroger/MultiverseEx26-7B-slerp",
|
|
"llama 3",
|
|
"ruslanmv",
|
|
"agents",
|
|
"traditional_chinese",
|
|
"mlabonne/Zebrafish-7B",
|
|
"mlp_speculator",
|
|
"pets",
|
|
"pose",
|
|
"Fine-tuning",
|
|
"Cantonese",
|
|
"xgenmm",
|
|
"Text-to-Speech",
|
|
"rwkv6",
|
|
"fast",
|
|
"quality",
|
|
"Quantized",
|
|
"zero-shot NER",
|
|
"npu",
|
|
"amd",
|
|
"autonomous driving",
|
|
"xlm-token",
|
|
"cambrian_llama",
|
|
"llava_qwen2",
|
|
"Blockchain",
|
|
"cypher",
|
|
"neo4j",
|
|
"regmix",
|
|
"deepfake",
|
|
"in-context learning",
|
|
"Question-Answer",
|
|
"fbgemm_fp8",
|
|
"sample-generation",
|
|
"stable-audio",
|
|
"transfer learning",
|
|
"nai",
|
|
"mental_health",
|
|
"Whisper",
|
|
"Speech",
|
|
"multimodal retrieval",
|
|
"aetherwiing/MN-12B-Starcannon-v3",
|
|
"Politics",
|
|
"affiliations",
|
|
"NovelAI",
|
|
"ijepa",
|
|
"gemma-2",
|
|
"matting",
|
|
"rknn",
|
|
"banglaLLM",
|
|
"banglaNLP",
|
|
"LLama",
|
|
"Foundation Model",
|
|
"Uncensored",
|
|
"dev-ops",
|
|
"developer",
|
|
"Locutusque/Hercules-6.1-Llama-3.1-8B",
|
|
"yolo11",
|
|
"purz",
|
|
"flux1.d",
|
|
"NeuralMahou",
|
|
"NIHAPPY",
|
|
"Flux-Dev",
|
|
"taxation",
|
|
"fiscalit\u00e9",
|
|
"GenAI",
|
|
"conversational ai",
|
|
"p3",
|
|
"Datasets",
|
|
"70b",
|
|
"public domain",
|
|
"computervision",
|
|
"housing",
|
|
"inference",
|
|
"fine-grained",
|
|
"1024px_based_image_size",
|
|
"GPTSoVITS",
|
|
"loi",
|
|
"So-VITS-SVC",
|
|
"Modeling",
|
|
"low-resource-language",
|
|
"DefinitionGeneration",
|
|
"definition-modeling",
|
|
"anvita",
|
|
"homer",
|
|
"Qandora",
|
|
"Sentient",
|
|
"tech",
|
|
"Rosmontis",
|
|
"\u8ff7\u8fed\u9999",
|
|
"Llama-CPP",
|
|
"bokm\u00e5l",
|
|
"qwq",
|
|
"bluesky",
|
|
"vtuber",
|
|
"unlearning",
|
|
"MilkDrop",
|
|
"Korean",
|
|
"notes",
|
|
"reconstruction",
|
|
"Chain-of-Thought Activation",
|
|
"tagger",
|
|
"rule34",
|
|
"ERP",
|
|
"humor",
|
|
"French",
|
|
"RobBERTje",
|
|
"transformer_vae",
|
|
"cel",
|
|
"fiu",
|
|
"gmw",
|
|
"torch==1.8.0",
|
|
"\u00e6l\u00e6ctra",
|
|
"ELECTRA-Small",
|
|
"replaced token detection",
|
|
"collaborative",
|
|
"answering",
|
|
"data2text",
|
|
"semeval2020",
|
|
"comve",
|
|
"hierarchical_model",
|
|
"parlaspeech",
|
|
"stateless transducer",
|
|
"Greek",
|
|
"TextClassification",
|
|
"speech2text2",
|
|
"character_bert",
|
|
"xlmindic",
|
|
"indoaryan",
|
|
"iso15919",
|
|
"jira",
|
|
"ga-IE",
|
|
"reinforcement learning",
|
|
"gpt-2",
|
|
"satflow",
|
|
"other-image-classification",
|
|
"npc-engine",
|
|
"nowcasting",
|
|
"llama-leaderboard",
|
|
"encoder_decoder",
|
|
"xls_r_repro_common_voice_tr",
|
|
"phongdtd/VinDataVLSP",
|
|
"html",
|
|
"LSTM",
|
|
"structured-data-classification",
|
|
"sentence-embeddings",
|
|
"spanish-english",
|
|
"RUDOLPH",
|
|
"morphology",
|
|
"SplinterModel",
|
|
"mongolian",
|
|
"distilt5",
|
|
"distilt5-qg",
|
|
"text-2-text-generation",
|
|
"question_answering",
|
|
"medicalimaging",
|
|
"belarusian",
|
|
"oral",
|
|
"roformer-v2",
|
|
"serbian",
|
|
"MTee",
|
|
"general",
|
|
"liltrobertalike",
|
|
"greaselm",
|
|
"multilingual model",
|
|
"non-commercial",
|
|
"seals/Ant-v0",
|
|
"seals/Hopper-v0",
|
|
"seals/Humanoid-v0",
|
|
"RoadRunnerNoFrameskip-v4",
|
|
"SeaquestNoFrameskip-v4",
|
|
"Humanoid-v3",
|
|
"deep-rl-course",
|
|
"seals/HalfCheetah-v0",
|
|
"seals/Swimmer-v0",
|
|
"vison",
|
|
"tranception",
|
|
"decoding",
|
|
"Poet",
|
|
"MsPacmanNoFrameskip-v4",
|
|
"document-understanding",
|
|
"tfhub",
|
|
"UAV",
|
|
"erzya",
|
|
"mordovian",
|
|
"plagiarism",
|
|
"conversations",
|
|
"humanities",
|
|
"social_science",
|
|
"computer_science",
|
|
"claude",
|
|
"observers",
|
|
"customer service",
|
|
"multi-domain",
|
|
"evaluating-dialogue-systems",
|
|
"knowledge-verification",
|
|
"multi-hop",
|
|
"query-based-summarization",
|
|
"optical-character-recognition",
|
|
"markets",
|
|
"academic",
|
|
"scientific text",
|
|
"Web3",
|
|
"research paper",
|
|
"stackoverflow",
|
|
"en-atc",
|
|
"stacked summaries",
|
|
"personality",
|
|
"Damage Risk",
|
|
"sec",
|
|
"SimpleAI",
|
|
"mxeval",
|
|
"transcripts",
|
|
"knowledge-base-qa",
|
|
"mental",
|
|
"dolly",
|
|
"automatic speech recognition",
|
|
"Spatial-Temporal",
|
|
"sharegpt",
|
|
"theorem-proving",
|
|
"geology",
|
|
"fraud",
|
|
"Genomics",
|
|
"hallucination",
|
|
"spotify",
|
|
"table-structure-recognition",
|
|
"a.",
|
|
"haiku",
|
|
"red teaming",
|
|
"parallel data",
|
|
"Histopathology",
|
|
"Histology",
|
|
"Digital Pathology",
|
|
"prompt injection",
|
|
"Bard",
|
|
"LLaMA-2",
|
|
"Vicuna",
|
|
"PaLM-2",
|
|
"math-word-problem",
|
|
"arithmetic-reasoning",
|
|
"algebraic-reasoning",
|
|
"numeric-common-sense",
|
|
"scientific-reasoning",
|
|
"abstract-scene",
|
|
"Environement",
|
|
"mt-evaluation",
|
|
"WMT",
|
|
"sentinel-1",
|
|
"data science",
|
|
"galgame",
|
|
"website",
|
|
"Safety",
|
|
"image captioning",
|
|
"document",
|
|
"Multimodal Learning",
|
|
"biomedicine",
|
|
"Livre des proc\u00e9dures fiscales",
|
|
"Code du travail",
|
|
"Code de commerce",
|
|
"Code mon\u00e9taire et financier",
|
|
"Code de la construction et de l'habitation",
|
|
"Code civil",
|
|
"Code de la consommation",
|
|
"Code des assurances",
|
|
"Code de la propri\u00e9t\u00e9 intellectuelle",
|
|
"Code de la commande publique",
|
|
"Code p\u00e9nal",
|
|
"mozilla",
|
|
"news articles",
|
|
"spatial",
|
|
"recipes",
|
|
"driving",
|
|
"Human",
|
|
"country",
|
|
"stabeldiffusion",
|
|
"facial recognition",
|
|
"documentation",
|
|
"offensive-language",
|
|
"code-mixed",
|
|
"creature-dataset",
|
|
"validation",
|
|
"policy",
|
|
"samromur",
|
|
"word frequencies",
|
|
"AIvtuber",
|
|
"VirtuaReal",
|
|
"web-text",
|
|
"plain language",
|
|
"easy-to-read language",
|
|
"semantics",
|
|
"esa",
|
|
"uci",
|
|
"dhivehi",
|
|
"fiscal",
|
|
"web-agent",
|
|
"Chloe",
|
|
"Bottega Veneta",
|
|
"Balenciaga",
|
|
"Chanel",
|
|
"flux dev",
|
|
"Llama 3.2 MOE",
|
|
"FLUX",
|
|
"deepseek_vl_v2",
|
|
"Super-Realism",
|
|
"code-solve",
|
|
"algorithm",
|
|
"qwen_base",
|
|
"bfcl",
|
|
"pattern recognition",
|
|
"chart reader",
|
|
"muiltimodal",
|
|
"unified-model",
|
|
"grok-1",
|
|
"cross-modal",
|
|
"Patronus AI",
|
|
"hallucination-detection",
|
|
"triangulum_1b",
|
|
"text_to_image",
|
|
"mambavision",
|
|
"rdt",
|
|
"Emu3",
|
|
"Qwen2-VL",
|
|
"Pixart-\u03b1",
|
|
"Kolors",
|
|
"Photorealistic",
|
|
"stable-diffusion-3.5-large",
|
|
"v6",
|
|
"erax",
|
|
"memes",
|
|
"LMM",
|
|
"Code Summarization",
|
|
"cryptocurrency",
|
|
"cantonese",
|
|
"vivit",
|
|
"gpt-neox",
|
|
"pipeline",
|
|
"extreme-multi-task",
|
|
"extreme-mtl",
|
|
"seamless_m4t_v2",
|
|
"vmistral",
|
|
"home",
|
|
"noticia",
|
|
"reward_model",
|
|
"phimoe",
|
|
"Inpainting",
|
|
"ncsoft",
|
|
"varco",
|
|
"hymba",
|
|
"flux.1-schnell",
|
|
"flux-merge",
|
|
"Wav2Vec2",
|
|
"DDSP-SVC",
|
|
"PartAI",
|
|
"ablated",
|
|
"ablation",
|
|
"nani",
|
|
"sentiment_analysis",
|
|
"multimodal-retrieval",
|
|
"music ai",
|
|
"grammatical error correction",
|
|
"text2text",
|
|
"kenlm",
|
|
"xls_r_pretrained",
|
|
"kb",
|
|
"tp",
|
|
"masked-token-prediction",
|
|
"bert-base-multilingual-cased",
|
|
"drugs",
|
|
"sentence_50agree",
|
|
"\u6587\u8a00\u6587",
|
|
"bioinfomatics",
|
|
"Speech Enhancement",
|
|
"Spoken language understanding",
|
|
"ECAPA",
|
|
"Sentence-Embedding",
|
|
"Similarity",
|
|
"financial-text-analysis",
|
|
"Business",
|
|
"Financial News",
|
|
"Sustainability",
|
|
"HiFIGAN",
|
|
"BERT2BERT",
|
|
"FLAN",
|
|
"prompting",
|
|
"license-plate-detection",
|
|
"math-aware",
|
|
"robots",
|
|
"lilt",
|
|
"maxim",
|
|
"VAE",
|
|
"Data Augmentation",
|
|
"handwriting-recognition",
|
|
"entity typing",
|
|
"galactica",
|
|
"text2text generation",
|
|
"textual-inversion",
|
|
"puli",
|
|
"textual inversion",
|
|
"graphs",
|
|
"LoRa",
|
|
"extractive",
|
|
"abstractive",
|
|
"Image Generation",
|
|
"STT",
|
|
"animal",
|
|
"geolocation",
|
|
"text retrieval",
|
|
"sentence-boundary-detection",
|
|
"latent diffusion",
|
|
"xmod",
|
|
"human_genome",
|
|
"matcha",
|
|
"baize",
|
|
"instructional",
|
|
"generative-adversarial-network",
|
|
"albertina-pt*",
|
|
"Text2Text-Generation",
|
|
"trading",
|
|
"encodec",
|
|
"beaver",
|
|
"locon",
|
|
"shap-e",
|
|
"idefics",
|
|
"upstage",
|
|
"music-captioning",
|
|
"Geospatial",
|
|
"synthetic instruction",
|
|
"kollama",
|
|
"llama-2-ko",
|
|
"Foundation model",
|
|
"multilingual-code-generation",
|
|
"plants",
|
|
"document analysis",
|
|
"unstructured document",
|
|
"computer_vision",
|
|
"fairseq2",
|
|
"SeamlessM4T",
|
|
"functions",
|
|
"icons",
|
|
"midi generation",
|
|
"automatic-speech-translation",
|
|
"foundation-model",
|
|
"vitmatte",
|
|
"PyLaia",
|
|
"artist",
|
|
"sparse sparsity quantized onnx embeddings int8",
|
|
"audio-captioning",
|
|
"streaming",
|
|
"m42",
|
|
"clinical-llm",
|
|
"Bode",
|
|
"Social Media",
|
|
"BlueLM",
|
|
"distilled-model",
|
|
"StableLM",
|
|
"causallm",
|
|
"openhermes",
|
|
"m2_bert",
|
|
"\u5c01\u795e\u699c",
|
|
"layout-to-image",
|
|
"wespeaker",
|
|
"orca2",
|
|
"nemotron-3",
|
|
"surrealism",
|
|
"kawaii",
|
|
"silly",
|
|
"magic",
|
|
"digital art",
|
|
"Storywriter",
|
|
"expressionism",
|
|
"landscapes",
|
|
"share4v",
|
|
"art style",
|
|
"pruna-engine",
|
|
"cities",
|
|
"full body",
|
|
"sorani",
|
|
"ultra",
|
|
"sentinel2",
|
|
"landsat",
|
|
"arabic ",
|
|
"audio2text",
|
|
"shadow",
|
|
"Megatron-LM",
|
|
"ctc",
|
|
"UBC",
|
|
"DLNLP",
|
|
"MachineMindset",
|
|
"cookinai/CatMacaroni-Slerp",
|
|
"hf_olmo",
|
|
"MRI",
|
|
"Weyaxi/OpenHermes-2.5-neural-chat-v3-3-openchat-3.5-1210-Slerp",
|
|
"EmbeddedLLM/Mistral-7B-Merge-14-v0.1",
|
|
"AI-B/UTENA-7B-UNA-V2",
|
|
"AI-B/UTENA-7B-NSFW-V2",
|
|
"orion",
|
|
"liminerity/Blur-7b-slerp-v0.1",
|
|
"has_space",
|
|
"liminerity/Blured-Ties-7B",
|
|
"freecs/ThetaWave-7B",
|
|
"Manga",
|
|
"Object Detection",
|
|
"Scepter",
|
|
"Solar",
|
|
"abideen/DareVox-7B",
|
|
"senseable/Westlake-7B-v2",
|
|
"vistral",
|
|
"meta-math/MetaMath-Mistral-7B",
|
|
"CultriX/MergeTrix-7B-v2",
|
|
"snorkelai/Snorkel-Mistral-PairRM-DPO",
|
|
"myanmar",
|
|
"cybersecwithai",
|
|
"ai4security",
|
|
"llmsecurity",
|
|
"VAGOsolutions/SauerkrautLM-7b-v1-mistral",
|
|
"chargoddard/loyal-piano-m7",
|
|
"free",
|
|
"freeai",
|
|
"SanjiWatsuki/Loyal-Toppy-Bruins-Maid-7B-DARE",
|
|
"ND911/EE-LMaid-7B-Slerp",
|
|
"flemmingmiguel/MBX-7B",
|
|
"chargoddard/loyal-piano-m7-cdpo",
|
|
"athirdpath/NSFW_DPO_vmgb-7b",
|
|
"kaitchup/Mayonnaise-4in1-022",
|
|
"judge",
|
|
"rishiraj/CatPPT-base",
|
|
"latex-ocr",
|
|
"Kukedlc/NeuTrixOmniBe-7B-model-remix",
|
|
"machinists/Mistral-7B-SQL",
|
|
"Zenith-7B-dpo-v2",
|
|
"Eclipse-13B-dpo",
|
|
"scholarly",
|
|
"traditional chinese",
|
|
"zh-hant",
|
|
"Kukedlc/Neural-4-ARC-7B-slerp",
|
|
"Kukedlc/Neural-4-GSM8K-7B-slerp",
|
|
"paulml/OGNO-7B",
|
|
"bunny-phi",
|
|
"\ud83c\udf7b",
|
|
"9B",
|
|
"marathi",
|
|
"gordicaleksa/YugoGPT",
|
|
"khanacademy",
|
|
"vc",
|
|
"dac",
|
|
"logo",
|
|
"Kukedlc/NeoCortex-7B-slerp",
|
|
"cognitivecomputations/samantha-mistral-7b",
|
|
"CorticalStack/shadow-clown-7B-dare",
|
|
"BryanSwk/LaserPipe-7B-SLERP",
|
|
"function-call",
|
|
"Kukedlc/NeuralGlitch-Yam-Peleg-7B-DT",
|
|
"StableDiffusionXL",
|
|
"voice conversion",
|
|
"block expansion",
|
|
"progressive mistral",
|
|
"arcee cpt",
|
|
"unity",
|
|
"rwitz/experiment26-truthy-iter-0",
|
|
"Hypersniper/The_Philosopher_Zephyr_7B",
|
|
"sayhan/OpenHermes-2.5-Strix-Philosophy-Mistral-7B-LoRA",
|
|
"AetherResearch/Cerebrum-1.0-7b",
|
|
"Kukedlc/SuperMente-7B-v2",
|
|
"nlpguy/AlloyIngotNeoX",
|
|
"automerger/YamShadow-7B",
|
|
"self-supervised",
|
|
"vortexmergekit",
|
|
"Problem Solving",
|
|
"AI Programming Assistant",
|
|
"mipha_phi",
|
|
"unsloth/mistral-7b-v0.2",
|
|
"Yuma42/KangalKhan-RawRuby-7B",
|
|
"nlpguy/T3QM7",
|
|
"PocketDoc/Dans-AdventurousWinds-Mk2-7b",
|
|
"Smuggling1710/Ak4ri-7b",
|
|
"Base Model",
|
|
"dbrx",
|
|
"all-in-one",
|
|
"lemonilia/LimaRP-Mistral-7B-v0.1",
|
|
"Weyaxi/Einstein-v5-v0.2-7B",
|
|
"preference_learning",
|
|
"educational",
|
|
"feature_extraction",
|
|
"hatespeech",
|
|
"R",
|
|
"Julia",
|
|
"chaoyi-wu/MedLLaMA_13B",
|
|
"lmsys/vicuna-13b-v1.3",
|
|
"Text-to-sql",
|
|
"lex-hue/Delexa-7b",
|
|
"Diffusion Models",
|
|
"sprites",
|
|
"yleo/EmertonMonarch-7B",
|
|
"keyword-extraction",
|
|
"merlinite",
|
|
"pyannet",
|
|
"bunny-llama",
|
|
"xtuner",
|
|
"vitpose",
|
|
"Phi-3",
|
|
"snowflake",
|
|
"style-bert-vits2",
|
|
"style-bert-vits2-jp-extra",
|
|
"childish",
|
|
"childish voice",
|
|
"text2audio",
|
|
"text to audio",
|
|
"64k",
|
|
"iMat",
|
|
"zero shot",
|
|
"docvqa",
|
|
"visual question answering",
|
|
"Mental Health",
|
|
"llama-3-8b",
|
|
"ddh0/OrcaMaid-v3-13b-32k",
|
|
"DavidAU/D_AU-Orac-13B-Tiefighter-slerp",
|
|
"Jayant9928/orpo_med_v3",
|
|
"skumar9/Llama-medx_v3",
|
|
"mantis",
|
|
"Uncensored conversation",
|
|
"Uncensored jokes",
|
|
"Uncensored romance",
|
|
"merges",
|
|
"PHP",
|
|
"phi3small",
|
|
"sdxl-flash",
|
|
"hyper",
|
|
"fast-sdxl",
|
|
"sd-community",
|
|
"general tasks",
|
|
"selm",
|
|
"finbert",
|
|
"dora",
|
|
"detoxification",
|
|
"llava_next_video",
|
|
"hpc",
|
|
"axonn",
|
|
"large_language_model",
|
|
"sec_data",
|
|
"continual_pre_training",
|
|
"penetration testing",
|
|
"texture",
|
|
"entity",
|
|
"entity disambiguation",
|
|
"depth-anything-v2",
|
|
"editing",
|
|
"openlm",
|
|
"OmnicromsBrain/StoryFusion-7B",
|
|
"Healthcare",
|
|
"Reward Model",
|
|
"TaMeR",
|
|
"groq",
|
|
"Solana",
|
|
"SmartContract",
|
|
"semi-realistic",
|
|
"FinGPT",
|
|
"Banks",
|
|
"Wealth Management",
|
|
"evf",
|
|
"Video Generative Model Training",
|
|
"Text-to-Video Diffusion Model Training",
|
|
"GDPR",
|
|
"Spatial Understanding",
|
|
"Self-supervised Learning",
|
|
"datadreamer",
|
|
"audio classification",
|
|
"Sequence-Classification",
|
|
"transliteration system",
|
|
"entity-relationship-extraction",
|
|
"news-analysis",
|
|
"autogptq",
|
|
"Knowledge Graphs",
|
|
"light-embed",
|
|
"scene generation",
|
|
"shell",
|
|
"BiRefNet",
|
|
"text-correction",
|
|
"word-sense-linking",
|
|
"lexical-semantics",
|
|
"high-quality",
|
|
"OpenAssistant",
|
|
"lighting",
|
|
"Deep Learning",
|
|
"goldfish",
|
|
"debugging",
|
|
"mplugowl3",
|
|
"network",
|
|
"videollama2_qwen2",
|
|
"SmolLM",
|
|
"ghost",
|
|
"foundation-models",
|
|
"golang",
|
|
"go",
|
|
"eagle_llama",
|
|
"Eagle",
|
|
"sd.cpp",
|
|
"stable-diffusion.cpp",
|
|
"Retrieval Augmented Generation",
|
|
"role-playing",
|
|
"novel-generation",
|
|
"minimind",
|
|
"float8_e4m3fn",
|
|
"HotpotQA",
|
|
"RNA",
|
|
"text2cypher",
|
|
"pii",
|
|
"lm-judge",
|
|
"anatomy",
|
|
"litgpt",
|
|
"litdata",
|
|
"oryx_qwen",
|
|
"lerobot",
|
|
"novelwriting",
|
|
"NASA",
|
|
"Named entity recognition",
|
|
"Articles",
|
|
"neuralmagic",
|
|
"llmcompressor",
|
|
"TW",
|
|
"jina-judge",
|
|
"brain",
|
|
"slang",
|
|
"esper",
|
|
"terraform",
|
|
"aws",
|
|
"gcp",
|
|
"architect",
|
|
"engineer",
|
|
"opus-mt-tc-bible",
|
|
"cryptology",
|
|
"cipher",
|
|
"emerald",
|
|
"welding",
|
|
"PHI",
|
|
"glm4",
|
|
"longwriter",
|
|
"cambrian_qwen",
|
|
"medembed",
|
|
"medical-embedding",
|
|
"clinical-embedding",
|
|
"4-bit precision",
|
|
"Fine-Tuning with LoRA",
|
|
"NT GenAI",
|
|
"ntgenai",
|
|
"lahnmah",
|
|
"NT Thai GPT",
|
|
"ntthaigpt",
|
|
"\u0e2b\u0e25\u0e32\u0e19\u0e21\u0e48\u0e32",
|
|
"NT Academy",
|
|
"VPTQ",
|
|
"vptq",
|
|
"LCARS",
|
|
"gpt_optimized",
|
|
"conversational skill",
|
|
"Pneuma",
|
|
"Allades",
|
|
"mergekit-community/L3.1-Pneuma-8B-v1",
|
|
"marvel",
|
|
"model_fusion",
|
|
"coding_assistant",
|
|
"creative_writing",
|
|
"latent_diffusion",
|
|
"long_context",
|
|
"agentic_AI",
|
|
"multi_domain",
|
|
"technical_reasoning",
|
|
"task_generalization",
|
|
"AI_tools",
|
|
"llmware-fx",
|
|
"llama 3.2",
|
|
"CohereForAI",
|
|
"Music",
|
|
"Generation",
|
|
"SmolLM2",
|
|
"webrl",
|
|
"webarena-lite",
|
|
"denoiser",
|
|
"Lappland",
|
|
"\u62c9\u666e\u5170\u5fb7",
|
|
"qiskit",
|
|
"hydra-project/ChatHercules-2.5-Mistral-7B",
|
|
"Nitral-Archive/Prima-Pastacles-7b",
|
|
"coherence",
|
|
"retro",
|
|
"segment anything",
|
|
"zero-shot matting",
|
|
"medical-embeddings",
|
|
"512px_based_image_size",
|
|
"llama-2-chat",
|
|
"SmolTalk",
|
|
"95b",
|
|
"encyclopedia",
|
|
"meme",
|
|
"Role-play",
|
|
"google-earth",
|
|
"3DXL",
|
|
"influencer",
|
|
"anomaly-detection",
|
|
"Magpie",
|
|
"Tulu3",
|
|
"Smollm",
|
|
"SLMs",
|
|
"Huggingface",
|
|
"Allenai",
|
|
"empathetic",
|
|
"masked-auto-encoding",
|
|
"turing",
|
|
"Priya",
|
|
"Teen-AI",
|
|
"Promptist-Instruct",
|
|
"DELLA-linear",
|
|
"Visualizations",
|
|
"dnotitia",
|
|
"MATH",
|
|
"higgs",
|
|
"llama-3.3",
|
|
"render",
|
|
"CAD",
|
|
"Blender",
|
|
"plonk",
|
|
"text to image",
|
|
"peer",
|
|
"automatic",
|
|
"conference",
|
|
"manuscript",
|
|
"openreview",
|
|
"model-stock",
|
|
"Qwen with Questions",
|
|
"summaries",
|
|
"DucHaiten",
|
|
"inappropriate",
|
|
"stories",
|
|
"sex",
|
|
"BeaverAI/mistral-doryV2-12b",
|
|
"for-entertainment-purposes-only",
|
|
"do-not-use-seriously",
|
|
"cannabis",
|
|
"HELVETE-X",
|
|
"Unfiltered-AI",
|
|
"Advanced-EI",
|
|
"character_creation",
|
|
"world-building",
|
|
"lore_writing",
|
|
"misogyny",
|
|
"Axon",
|
|
"Elixir",
|
|
"DistilBert",
|
|
"Dialect",
|
|
"Tweets",
|
|
"rm-vallader",
|
|
"Russian-speech-corpus",
|
|
"afa",
|
|
"cpp",
|
|
"iir",
|
|
"ine",
|
|
"itc",
|
|
"sem",
|
|
"sla",
|
|
"urj",
|
|
"sentence segmentation",
|
|
"beto",
|
|
"Slovak GPT-J",
|
|
"fake",
|
|
"translation Cszech Deustch model",
|
|
"translation Cszech English model",
|
|
"translation Cszech Spanish model",
|
|
"translation Cszech French model",
|
|
"translation Cszech Italian model",
|
|
"translation Cszech Swedish model",
|
|
"translation Deustch English model",
|
|
"translation Deustch Spanish model",
|
|
"translation Deustch French model",
|
|
"translation Deustch Italian model",
|
|
"translation Deustch Swedish model",
|
|
"translation English Cszech model",
|
|
"translation English Deustch model",
|
|
"translation English Italian model",
|
|
"translation French Cszech model",
|
|
"translation French English model",
|
|
"translation French Spanish model",
|
|
"translation French Italian model",
|
|
"translation French Swedish model",
|
|
"translation Italian Cszech model",
|
|
"translation Italian Deustch model",
|
|
"translation Italian English model",
|
|
"translation Italian Spanish model",
|
|
"translation Italian French model",
|
|
"translation Italian Swedish model",
|
|
"translation Swedish Cszech model",
|
|
"translation Swedish Deustch model",
|
|
"translation Swedish English model",
|
|
"translation Swedish Spanish model",
|
|
"translation Swedish French model",
|
|
"translation Swedish Italian model",
|
|
"ChatBot",
|
|
"openslr_SLR53",
|
|
"qg",
|
|
"wolof",
|
|
"Bible",
|
|
"simcls",
|
|
"torchscript",
|
|
"FastNN",
|
|
"malayalam",
|
|
"social_media",
|
|
"dacy",
|
|
"pos tagging",
|
|
"morphological analysis",
|
|
"named entity linking",
|
|
"named entity disambiguation",
|
|
"openslr_SLR66",
|
|
"cyrillic",
|
|
"historic french",
|
|
"COVID-19",
|
|
"irony",
|
|
"conditional-image-generation",
|
|
"clip-vision-marian",
|
|
"elasticbert",
|
|
"Multi-exit-BERT",
|
|
"azureml",
|
|
"intent classification",
|
|
"pt_BR",
|
|
"wobert",
|
|
"lassl",
|
|
"sci",
|
|
"nyc",
|
|
"films",
|
|
"banking",
|
|
"mudes",
|
|
"mental-health",
|
|
"mobile app descriptions",
|
|
"playstore",
|
|
"ehr",
|
|
"wavlm_libri_finetune",
|
|
"mozilla-foundation/common_voice_3_0",
|
|
"casual language modeling",
|
|
"parsbert",
|
|
"query-paraphrasing",
|
|
"reading-comprehension",
|
|
"BabyBERTa",
|
|
"RNN",
|
|
"lfqa",
|
|
"hindi-english",
|
|
"semantic-similarity",
|
|
"classics",
|
|
"simcse",
|
|
"sbert",
|
|
"faroese",
|
|
"distractor",
|
|
"dstc10",
|
|
"singapore",
|
|
"singlish",
|
|
"manglish",
|
|
"masked-image-modeling",
|
|
"m2m100-12B",
|
|
"abdusahmbzuai/arabic_speech_massive_300hrs",
|
|
"cyberbullying",
|
|
"hunflair",
|
|
"text-to-rating",
|
|
"QG",
|
|
"xgboost",
|
|
"r3m",
|
|
"quality estimation",
|
|
"document sections",
|
|
"document classification",
|
|
"language classification",
|
|
"groupvit",
|
|
"domain adaptation",
|
|
"collaborative-filtering",
|
|
"recommender",
|
|
"mT5_multilingual_XLSum",
|
|
"ImageClassification",
|
|
"molecule-generation",
|
|
"cheminformatics",
|
|
"biochemical-language-models",
|
|
"xlmroberta",
|
|
"Caribbean dialect",
|
|
"paraphrase-detection",
|
|
"owlvit",
|
|
"formality transfer",
|
|
"PROP",
|
|
"Pretrain4IR",
|
|
"btcv",
|
|
"Hindi",
|
|
"ZEN",
|
|
"HTR",
|
|
"face alignment",
|
|
"facial landmark point",
|
|
"pose estimation",
|
|
"tokenizer only",
|
|
"luxembourgish",
|
|
"l\u00ebtzebuergesch",
|
|
"adverse-drug-events",
|
|
"social-media-mining-for-health",
|
|
"SMM4H",
|
|
"\u4e2d\u6587",
|
|
"masked language modeling",
|
|
"albert_act",
|
|
"software",
|
|
"rejection-sampling",
|
|
"large-language-model",
|
|
"screenshots",
|
|
"Satellite",
|
|
"Asia",
|
|
"identification",
|
|
"idioms",
|
|
"conversational-qa",
|
|
"meaning-representation-to-text",
|
|
"knowledge-base",
|
|
"probing",
|
|
"fake-news-detection",
|
|
"superglue",
|
|
"audio-slot-filling",
|
|
"code-switching",
|
|
"cleaned",
|
|
"long-texts",
|
|
"children education",
|
|
"oxford",
|
|
"citation",
|
|
"text-detection",
|
|
"image-text pairs",
|
|
"stackexchange",
|
|
"commonsense reasoning",
|
|
"academic integrity",
|
|
"theses",
|
|
"acl",
|
|
"headline",
|
|
"gender bias",
|
|
"social bias",
|
|
"edgar",
|
|
"filings",
|
|
"10K",
|
|
"10-K",
|
|
"Self Driving",
|
|
"public",
|
|
"selfies",
|
|
"Gaming",
|
|
"Retail",
|
|
"Aerial",
|
|
"layout-segmentation",
|
|
"DocLayNet",
|
|
"Financial-Reports",
|
|
"Manuals",
|
|
"Scientific-Articles",
|
|
"Laws",
|
|
"Regulations",
|
|
"Patents",
|
|
"Government-Tenders",
|
|
"preference model",
|
|
"microbiome",
|
|
"argument mining",
|
|
"television",
|
|
"steam",
|
|
"gpt-4",
|
|
"nutrition",
|
|
"Jailbreak",
|
|
"Last-mile Delivery",
|
|
"molecule",
|
|
"balanced",
|
|
"websites",
|
|
"music-to-text",
|
|
"function call",
|
|
"ehartford",
|
|
"embodied ai",
|
|
"unit test",
|
|
"shakespeare",
|
|
"arithmetics",
|
|
"logos",
|
|
"rdf",
|
|
"ontology",
|
|
"harmless",
|
|
"occultism",
|
|
"statistical-reasoning",
|
|
"crawl",
|
|
"papers",
|
|
"question-answer",
|
|
"haerae",
|
|
"4d",
|
|
"History",
|
|
"aerial",
|
|
"typescript",
|
|
"outdoor",
|
|
"weather",
|
|
"mathematical-reasoning",
|
|
"LVLM",
|
|
"statistics",
|
|
"culture",
|
|
"multilabel classification",
|
|
"vdf",
|
|
"vector-io",
|
|
"vector-dataset",
|
|
"vector-embeddings",
|
|
"Retrieval",
|
|
"retrieval-augmented generation",
|
|
"Synthetic",
|
|
"dialogue-system",
|
|
"internet",
|
|
"sar",
|
|
"Benchmarks",
|
|
"conversational QA",
|
|
"multi-turn QA",
|
|
"QA with context",
|
|
"Alignment-Lab-AI",
|
|
"Document Retrieval",
|
|
"documents",
|
|
"RGB",
|
|
"LLaVA-NeXt",
|
|
"refusal",
|
|
"Entertainment",
|
|
"articles",
|
|
"droit-fran\u00e7ais",
|
|
"code-civil",
|
|
"juris",
|
|
"Code g\u00e9n\u00e9ral des imp\u00f4ts",
|
|
"Code de la d\u00e9fense",
|
|
"Code de l'action sociale et des familles",
|
|
"Code du cin\u00e9ma et de l'image anim\u00e9e",
|
|
"Code des impositions sur les biens et services",
|
|
"Ocean",
|
|
"visual novel",
|
|
"adversarial robustness",
|
|
"yelp",
|
|
"semisynthetic",
|
|
"africa",
|
|
"anti-spoofing",
|
|
"arknights",
|
|
"fma",
|
|
"free-music-archive",
|
|
"humour",
|
|
"dialogues",
|
|
"face recognition",
|
|
"chat-instruct",
|
|
"llama-3.1-405b",
|
|
"lezghian",
|
|
"Software Analysis",
|
|
"Human Pose and Shape Estimation",
|
|
"Synthetic Data",
|
|
"devops",
|
|
"lidar",
|
|
"manuscripts",
|
|
"blood",
|
|
"so100",
|
|
"tutorial",
|
|
"india",
|
|
"github",
|
|
"drone",
|
|
"computer vison",
|
|
"temporal",
|
|
"vectors",
|
|
"clusterisation",
|
|
"flux1.1",
|
|
"flux1",
|
|
"imagen3",
|
|
"jsonl",
|
|
"radio",
|
|
"patent-summarization",
|
|
"news-category-classification",
|
|
"gender-bias",
|
|
"constituency-parsing",
|
|
"causal-reasoning",
|
|
"speech-modeling",
|
|
"argument-mining",
|
|
"abbreviation-detection",
|
|
"conservation",
|
|
"movie reviews",
|
|
"sentence similarity",
|
|
"metaphor-classification",
|
|
"toxic comments",
|
|
"unsplash",
|
|
"kids",
|
|
"pretraining-with-human-feedback",
|
|
"short answer feedback",
|
|
"maps",
|
|
"masri",
|
|
"masri-project",
|
|
"malta",
|
|
"crowd-sourced icelandic",
|
|
"icelandic speech",
|
|
"iceland",
|
|
"demographic",
|
|
"doc2query--",
|
|
"low-resource",
|
|
"Reverse Engineered",
|
|
"faiss",
|
|
"adult",
|
|
"occlusion",
|
|
"face detection",
|
|
"vision-and-language",
|
|
"fake news",
|
|
"student performance",
|
|
"arXiv.org",
|
|
"publication",
|
|
"preprint",
|
|
"section",
|
|
"wikification",
|
|
"dogs",
|
|
"anaphora",
|
|
"mode classification",
|
|
"renumics",
|
|
"shopee",
|
|
"complex",
|
|
"stopwords",
|
|
"keyword2",
|
|
"keyword1",
|
|
"natsql",
|
|
"sql finetune",
|
|
"langchain-docs",
|
|
"binary-sentiment-analysis",
|
|
"mgame",
|
|
"machine reading",
|
|
"morphological-inflection",
|
|
"Non-fungible Tokens",
|
|
"Crypto",
|
|
"keywords-extraction",
|
|
"spectrogram",
|
|
"dialogue segmentation",
|
|
"Dior",
|
|
"Hermes",
|
|
"Blickers",
|
|
"taiga",
|
|
"tayga",
|
|
"ghana-news",
|
|
"pinyin",
|
|
"mining",
|
|
"UltraRealism",
|
|
"RAW",
|
|
"4K",
|
|
"virtual try-off",
|
|
"triangulum_10b",
|
|
"video-to-audio",
|
|
"triangulum_5b",
|
|
"social-media-analysis",
|
|
"customer-feedback",
|
|
"product-reviews",
|
|
"brand-monitoring",
|
|
"intel/auto-round",
|
|
"instant-voice-cloning",
|
|
"kolors",
|
|
"GOT",
|
|
"ocr2.0",
|
|
"jina_clip",
|
|
"eva02",
|
|
"Contact Doctor",
|
|
"Llama 3",
|
|
"nvembed",
|
|
"qwen2vl",
|
|
"4x7B",
|
|
"32 bit enhanced",
|
|
"float 32 quants",
|
|
"mistral MOE",
|
|
"granite-tsfm",
|
|
"tinytimemixer",
|
|
"RAGatouille",
|
|
"minicpm3",
|
|
"template",
|
|
"erax-vl-2B",
|
|
"4x3B",
|
|
"Cute",
|
|
"Girls",
|
|
"Barons",
|
|
"juaner0211589",
|
|
"clinicaltrials",
|
|
"PyLate",
|
|
"Explain code",
|
|
"sentiment classification",
|
|
"Object detection",
|
|
"tvlt",
|
|
"deberta-v3-large",
|
|
"dghs-imgutils",
|
|
"pixelart",
|
|
"single image depth estimation",
|
|
"real_time",
|
|
"whisperkit",
|
|
"diffusion distillation",
|
|
"lrm_generator",
|
|
"IP-Adapter",
|
|
"kosmos-2.5",
|
|
"audiogen",
|
|
"reality",
|
|
"ko_leaderboard",
|
|
"SVDQuant",
|
|
"INT4",
|
|
"FLUX.1",
|
|
"Retro",
|
|
"computer use",
|
|
"PG-13",
|
|
"LLM-as-a-Judge",
|
|
"OBJ",
|
|
"Programming",
|
|
"Adapter",
|
|
"2Kpx_based_image_size",
|
|
"mochi",
|
|
"optimizer_states",
|
|
"minGRU",
|
|
"hf_integration",
|
|
"embedding-model",
|
|
"Applio",
|
|
"monster",
|
|
"coder",
|
|
"library",
|
|
"jap",
|
|
"trk",
|
|
"bert-fa",
|
|
"bert-persian",
|
|
"persian-lm",
|
|
"music-modeling",
|
|
"Question Generation",
|
|
"herbert",
|
|
"Diseases",
|
|
"passage reranking",
|
|
"aragpt2",
|
|
"t5-base",
|
|
"perplexity",
|
|
"n-gram",
|
|
"kneser-ney",
|
|
"bigscience",
|
|
"ai-msgbot",
|
|
"EDSR",
|
|
"bert-large",
|
|
"flaubert-large",
|
|
"recipe-generation",
|
|
"threat hunting",
|
|
"threat intelligence",
|
|
"array",
|
|
"of",
|
|
"crosslingual",
|
|
"chemist",
|
|
"drug design",
|
|
"common sense",
|
|
"\u53e4\u6587",
|
|
"gene",
|
|
"Recognition",
|
|
"WSJ02Mix",
|
|
"xvectors",
|
|
"math learning",
|
|
"\u00daFAL",
|
|
"biolinkbert",
|
|
"camembert-base",
|
|
"PyABSA",
|
|
"cyclegan",
|
|
"RE",
|
|
"entity mention detection",
|
|
"EMD",
|
|
"financial-emotion-analysis",
|
|
"extra_trees",
|
|
"hupd",
|
|
"synthesis",
|
|
"coqui.ai",
|
|
"Grapheme-to-Phoneme",
|
|
"vehicle-detection",
|
|
"DeBERTa",
|
|
"unified model",
|
|
"SpeechT5",
|
|
"Voice Conversion",
|
|
"grammar-correction",
|
|
"switch_transformers",
|
|
"waifu-diffusion",
|
|
"ai4bharat",
|
|
"\ud55c\uad6d\uc5b4",
|
|
"wildcard",
|
|
"synthwave",
|
|
"kurrent",
|
|
"swin2sr",
|
|
"stable-Diffusion",
|
|
"AraBERT",
|
|
"safety-checker",
|
|
"sygil-devs",
|
|
"protogen",
|
|
"disco-diffusion",
|
|
"graphormer",
|
|
"fp16",
|
|
"document summary",
|
|
"Woman",
|
|
"text2img",
|
|
"SD",
|
|
"Lora",
|
|
" stable-diffusion",
|
|
"Grapefruit",
|
|
"reward-model",
|
|
"hifigan",
|
|
"hate_speech",
|
|
"Document Question Answering",
|
|
"truecasing",
|
|
"InvertedPendulum-v2",
|
|
"veterinary",
|
|
"OpenNiji",
|
|
"Niji",
|
|
"Stylised",
|
|
"NorBERT",
|
|
"webui",
|
|
"true-casing",
|
|
"wrime",
|
|
"mert_model",
|
|
"stable_diffusion",
|
|
"pcdet",
|
|
"spelling correction",
|
|
"Google",
|
|
"Amazon",
|
|
"gpt_neox_reward_model",
|
|
"FunASR",
|
|
"moss",
|
|
"video-captioning",
|
|
"jax-diffusers-event",
|
|
"doctor",
|
|
"scat",
|
|
"textual_inversion",
|
|
"real",
|
|
"loha",
|
|
"albertina-ptpt",
|
|
"albertina-ptbr",
|
|
"uav",
|
|
"mplug-owl",
|
|
"chibi",
|
|
"lokr",
|
|
"traits",
|
|
"table detection",
|
|
"archive",
|
|
"KoLLaVA",
|
|
"glaucoma",
|
|
"unet",
|
|
"reinforcement-learning-from-human-feedback",
|
|
"qrcode",
|
|
"RVC v2",
|
|
"Audio-to-Audio",
|
|
"punctuation restoration",
|
|
"mmsegmentation",
|
|
"Sentinel-2",
|
|
"XLSR",
|
|
"sentence transformers",
|
|
"VITS",
|
|
"tensorrt",
|
|
"ted-deberta-v2",
|
|
"\u751f\u6210",
|
|
"blacklight",
|
|
"neon",
|
|
"absolute-realism",
|
|
"automatic-audio-captioning",
|
|
"audio-based-storytelling",
|
|
"speech-audio-coreasoning",
|
|
"auditory understanding",
|
|
"seamless_m4t",
|
|
"speech-generation",
|
|
"hack",
|
|
"D&D",
|
|
"portraits",
|
|
"42dot_llm",
|
|
"cotracker",
|
|
"entity-recognition",
|
|
"printed",
|
|
"rock",
|
|
"fauna",
|
|
"flora",
|
|
"startups",
|
|
"passage-reranking",
|
|
"flan-t5",
|
|
"plamo",
|
|
"InternLMXComposer",
|
|
"gptneo",
|
|
"ecology",
|
|
"mixformer-sequential",
|
|
"Voice2Voice",
|
|
"leolm",
|
|
"metaclip",
|
|
"instance segmentation",
|
|
"retnet",
|
|
"pickle",
|
|
"GO",
|
|
"CHECKPOINT",
|
|
"financial sentiment analysis",
|
|
"Entity Linking",
|
|
"SD1.5",
|
|
"spherical linear interpolation merge",
|
|
"zephyr",
|
|
"naberius",
|
|
"FLOR",
|
|
"roboflow-universe",
|
|
"human-detection",
|
|
"OpenCLIP",
|
|
"reco",
|
|
"cards",
|
|
"sdxl style lora",
|
|
"programming-language",
|
|
"Yi-34B-200K",
|
|
"language-detection",
|
|
"comic book",
|
|
"sticker",
|
|
"spooky",
|
|
"oil painting",
|
|
"stars",
|
|
"planets",
|
|
"colorful",
|
|
"watercolor",
|
|
"digital painting",
|
|
"deepvision",
|
|
"semirealistic",
|
|
"impressionism",
|
|
"abstract",
|
|
"miniatures",
|
|
"floods",
|
|
"femr",
|
|
"Medicine",
|
|
"FinBERT",
|
|
"FinTwitBERT",
|
|
"financial-analysis",
|
|
"water",
|
|
"foreground",
|
|
"japan",
|
|
"weather-forecasting",
|
|
"solar-ko",
|
|
"African",
|
|
"Chaeetah",
|
|
"dcase-challenge",
|
|
"vision language",
|
|
"ps1 style",
|
|
"llm-agent",
|
|
"openchat/openchat-3.5-1210",
|
|
"defect detection",
|
|
"electrical engineering",
|
|
"invest",
|
|
"telechat",
|
|
"slimsam",
|
|
"medical-imaging",
|
|
"genome",
|
|
"udkai/Garrulus",
|
|
"Deutsch",
|
|
"Clustering",
|
|
"Diarisation",
|
|
"liminerity/Blur-7b-v1.21",
|
|
"Solar Moe",
|
|
"222gate/BrurryDog-7b-v0.1",
|
|
"SanjiWatsuki/Lelantos-DPO-7B",
|
|
"uonlp",
|
|
"Viet-Mistral",
|
|
"internlmxcomposer2",
|
|
"distil-whisper",
|
|
"burmese",
|
|
"zysec.ai",
|
|
"malware analysis",
|
|
"exploitdev",
|
|
"ai4good",
|
|
"aisecurity",
|
|
"mlabonne/DareBeagle-7B-v2",
|
|
"\u8349\u8599\u5be7\u3005",
|
|
"pjsk",
|
|
"\u8349\u8599\u5b81\u5b81",
|
|
"\u30d7\u30ed\u30bb\u30ab",
|
|
"prsk",
|
|
"\u5b81\u5b81",
|
|
"image restoration",
|
|
"pose-estimation",
|
|
"obb",
|
|
"yolov3",
|
|
"yolov9",
|
|
"aerial imagery",
|
|
"watermark",
|
|
"Aditya685/upshot-sih",
|
|
"ponyxl",
|
|
"safetyguard",
|
|
"komodo",
|
|
"speech separation",
|
|
"trendyol",
|
|
"jondurbin/bagel-dpo-34b-v0.2",
|
|
"abacusai/MetaMath-Bagel-DPO-34B",
|
|
"tamil",
|
|
"common-canvas",
|
|
"Voyage",
|
|
"RJuro/munin-neuralbeagle-7b",
|
|
"sparsetral",
|
|
"Eric111/AlphaMayo",
|
|
"paulml/DPOB-INMTOB-7B",
|
|
"LORA",
|
|
"Chatgpt",
|
|
"liminerity/Neurotic-Momningojask-slerp",
|
|
"liminerity/Omningotex-7b-slerp",
|
|
"backbone",
|
|
"liminerity/1",
|
|
"Inv/Konstanta-7B",
|
|
"allstax/AI-G-Expander-v6",
|
|
"voice-cloning",
|
|
"DAC",
|
|
"ui",
|
|
"Kukedlc/NeuralMarioMonarch-7B-slerp",
|
|
"kviai",
|
|
"Image-to-Text Retrieval",
|
|
"Text-To-Image Retrieval",
|
|
"CultriX/NeuralTrixlaser-bf16",
|
|
"indic",
|
|
"vendor-names",
|
|
"zip-codes",
|
|
"rl",
|
|
"eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO-v3",
|
|
"Kukedlc/NeuralExperiment-7b-MagicCoder-v7",
|
|
"ser",
|
|
"msp-podcast",
|
|
"Corianas/Neural-Mistral-7B",
|
|
"Text-To-Image",
|
|
"MediaTek-Research/Breeze-7B-Instruct-v1_0",
|
|
"ammarali32/multi_verse_model",
|
|
"berturk",
|
|
"lstm",
|
|
"BioMistral/BioMistral-7B-DARE",
|
|
"meowgpt",
|
|
"splittic",
|
|
"samir-fama/FernandoGPT-v1",
|
|
"mahiatlinux/MasherAI-7B-v4",
|
|
"mohsinmubaraksk/Beast-Mixed",
|
|
"image-synthesis",
|
|
"wavelet-transform",
|
|
"mvpmaster/PearlMath-lafted-7b-slerp",
|
|
"Locutusque/NeuralHyperion-2.0-Mistral-7B",
|
|
"mvpmaster/NeuralMaths-lafted-7b-slerp",
|
|
"mvpmaster/nddmp-kellemar-KrishnaHercules-7b-slerp",
|
|
"mossformer2",
|
|
"eldogbbhed/NeuralMonarchCoderPearlBeagle",
|
|
"Gille/StrangeMerges_42-7B-dare_ties",
|
|
"swallow",
|
|
"dhyay/mistral_codev2_3k",
|
|
"Kukedlc/Neural-Krishna-Multiverse-7b-v3",
|
|
"Kukedlc/NeuTrixOmniBe-DPO",
|
|
"MatthieuJ/Jason1903_SLERP",
|
|
"Gille/StrangeMerges_30-7B-slerp",
|
|
"mlabonne/UltraMerge-7B",
|
|
"Smuggling1710/WestLakev2-IreneRP-Neural-7B-slerp",
|
|
"Nitral-AI/Eris_PrimeV3.075-Vision-7B",
|
|
"ml-4m",
|
|
"bobofrut/ladybird-base-7B-v8",
|
|
"Q-bert/MetaMath-Cybertron-Starling",
|
|
"ozayezerceli/BetterSaul-7B-slerp",
|
|
"kettleguts/zephyr-7b-beta_sparse05",
|
|
"kaist-ai/mistral-orpo-beta",
|
|
"Film",
|
|
"Photo",
|
|
"wildzzz",
|
|
"agritech",
|
|
"mplug_docowl",
|
|
"llm_content_detection",
|
|
"AI_detection",
|
|
"AI-Sweden-Models/tyr",
|
|
"neph1/bellman-7b-mistral-instruct-v0.2",
|
|
"matcha-tts",
|
|
"acoustic modelling",
|
|
"multispeaker",
|
|
"medialbertina-ptpt",
|
|
"european portuguese",
|
|
"ESCO",
|
|
"occupation coding",
|
|
"kz",
|
|
"MaziyarPanahi/Calme-7B-Instruct-v0.2",
|
|
"allknowingroger/LadybirdGonzo-7B-slerp",
|
|
"Ksgk-fy/M7Percival_010.14-0.33-0.6-0.72-0.02-0.65-7B",
|
|
"persona",
|
|
"foredoomed",
|
|
"passthrough_merge",
|
|
"starling",
|
|
"erebus",
|
|
"cockatrice",
|
|
"holodeck",
|
|
"limarp",
|
|
"koboldai",
|
|
"Clickbait",
|
|
"musilingo",
|
|
"young children",
|
|
"MaziyarPanahi/openchat_3.5-16k-Mistral-7B-Instruct-v0.2-slerp",
|
|
"fterry/FofoNet-DolphinChat-slerp",
|
|
"vgorce/MarcoroNeuralChat-7B-slerp",
|
|
"img2latex",
|
|
"openba",
|
|
"allknowingroger/AutoLimmy-7B-slerp",
|
|
"allknowingroger/StarlingDolphin-7B-slerp",
|
|
"recurrent_gemma",
|
|
"PixArt-\u03a3",
|
|
"FPHam/Karen_TheEditor_V2_STRICT_Mistral_7B",
|
|
"allknowingroger/RasGullaINEX12-7B-slerp",
|
|
"cstr/Spaetzle-v61-7b",
|
|
"cstr/Spaetzle-v53-7b",
|
|
"AlekseiPravdin/KSI-RP-NSK-128k-7B",
|
|
"grimjim/fireblossom-32K-7B",
|
|
"two stage dpo",
|
|
"phobert",
|
|
"llm-security",
|
|
"llama38b",
|
|
"NorskGPT",
|
|
"Phi-3-mini",
|
|
"video LLM",
|
|
"storm",
|
|
"Human Preference Alignment",
|
|
"PEFT",
|
|
"pythorch",
|
|
"llamantino",
|
|
"bunny-phi3",
|
|
"Female",
|
|
"ViT",
|
|
"Cpp",
|
|
"JS",
|
|
"MySql",
|
|
"imputation",
|
|
"Academic",
|
|
"Papers",
|
|
"Arxiv",
|
|
"japanese input",
|
|
"kana kanji conversion",
|
|
"enko",
|
|
"openpose",
|
|
"gender-classification",
|
|
"Theta Scaling",
|
|
"Big Patents",
|
|
"RoPE",
|
|
"sustainability",
|
|
"governance",
|
|
"bf16",
|
|
"ssd-1b",
|
|
"Stock Market",
|
|
"local",
|
|
"float32",
|
|
"space whale",
|
|
"speaker-separation",
|
|
"speech-separation",
|
|
"rerank",
|
|
"ibm-granite-code",
|
|
"tool-using",
|
|
"latex",
|
|
"telegram",
|
|
"drug discovery",
|
|
"mdlm",
|
|
"TCM",
|
|
"proprime",
|
|
"videollama2_mistral",
|
|
"value alignment",
|
|
"material",
|
|
"roberta-large",
|
|
"Mamba",
|
|
"Mamba-2",
|
|
"SSM",
|
|
"Emotionally Intelligent",
|
|
"classifier",
|
|
"tool-calling",
|
|
"agentic",
|
|
"personal",
|
|
"Sa\u011fl\u0131k",
|
|
"tensorart",
|
|
"violence-detection",
|
|
"apple",
|
|
"ane",
|
|
"gta",
|
|
"gta6",
|
|
"online video understanding",
|
|
"Time-series",
|
|
"PyTorch, Transformers",
|
|
"Yuna AI",
|
|
"EliTA Enhanced",
|
|
"companion",
|
|
"girlfriend",
|
|
"dust3r",
|
|
"Automated Peer Reviewing",
|
|
"OG_finetune_merge",
|
|
"cosplay",
|
|
"qwen-2",
|
|
"cogvlm--video",
|
|
"Lynx",
|
|
"llmware-rag",
|
|
"lineart",
|
|
"set-encoder",
|
|
"semiconductor",
|
|
"Data Protection",
|
|
"Phi-2",
|
|
"sciences",
|
|
"bunny",
|
|
"hebrew",
|
|
"masked-language-model",
|
|
"Knesset",
|
|
"composed image retrieval",
|
|
"image retrieval",
|
|
"acmmm2024",
|
|
"Mistral_Star",
|
|
"Mistral_Quiet",
|
|
"Token-Classification",
|
|
"SpydazWeb-AI",
|
|
"punjabi shahmukhi",
|
|
"punjabi gurmukhi",
|
|
"punjabi transliteration",
|
|
"punjabi gur to shahmukhi",
|
|
"punjabi transliteration system",
|
|
"Hyper-SDXL 8steps",
|
|
"multi-step merge",
|
|
"emotion classification",
|
|
"tabular data",
|
|
"py-feat",
|
|
"product",
|
|
"nl2bash",
|
|
"make-a-shape",
|
|
"vision transformer",
|
|
"spam-detection",
|
|
"Medusa",
|
|
"Speculative Decoding",
|
|
"shape_opt",
|
|
"Image-generation",
|
|
"pytoch",
|
|
"semantic parsing",
|
|
"Generative AI",
|
|
"3dtopia-xl",
|
|
"backgrounds",
|
|
"collaborative filtering",
|
|
"Tanuki",
|
|
"instruction following",
|
|
"nostalgia",
|
|
"story telling",
|
|
"ultra high precision",
|
|
"Bilingual",
|
|
"animagine",
|
|
"skin",
|
|
"natural language",
|
|
"Meta",
|
|
"taivisionlm",
|
|
"rene",
|
|
"cartesia",
|
|
"Seq2Seq",
|
|
"cats",
|
|
"trigger",
|
|
"covid",
|
|
"font",
|
|
"the protoart",
|
|
"pencil",
|
|
"chatqa-2",
|
|
"control-vector",
|
|
"qwen2vlm",
|
|
"VLLM",
|
|
"gpt-neo-x",
|
|
"llmware-encoder",
|
|
"vit_b",
|
|
"stable-diffusion-xl-lightning",
|
|
"p7",
|
|
"llava_jamba",
|
|
"contracts",
|
|
"Ultrachat",
|
|
"motion planning",
|
|
"flux schnell",
|
|
"low-resource-languages",
|
|
"OneGen",
|
|
"prototype",
|
|
"llama1",
|
|
"esthetic",
|
|
"fintech",
|
|
"gLM2",
|
|
"optical-flow-estimation",
|
|
"cleverboi",
|
|
"Conversational AI",
|
|
"Mistral-7B",
|
|
"cogvideox-fun",
|
|
"alibaba-pai",
|
|
"Weather & Climate",
|
|
"Web",
|
|
"llava_cohere",
|
|
"openCLIP",
|
|
"sami",
|
|
"nepali",
|
|
"politica",
|
|
"music llama",
|
|
"TextGeneration",
|
|
"eeg",
|
|
"image-processing",
|
|
"neuroscience",
|
|
"genz",
|
|
"NVLM_D",
|
|
"NVLM",
|
|
"Abliterated",
|
|
"llamaify",
|
|
"esper-2",
|
|
"1b",
|
|
"cogvideox-diffusers",
|
|
"fire",
|
|
"tost",
|
|
"ComfyUI",
|
|
"Animation",
|
|
"wala",
|
|
"genshin-impact",
|
|
"hoyoverse",
|
|
"80s",
|
|
"1980s",
|
|
"sign",
|
|
"light",
|
|
"llmware-vision",
|
|
"colonoscopy",
|
|
"polyp",
|
|
"ethereal",
|
|
"occult",
|
|
"vintage",
|
|
"COCOM",
|
|
"glif",
|
|
"hi-res",
|
|
"yolov11",
|
|
"p2",
|
|
"vjepa",
|
|
"medtech",
|
|
"HealthGPT",
|
|
"Star-Trek",
|
|
"128k-Context",
|
|
"drugdiscovery",
|
|
"llama3.2 1B",
|
|
"llama3.1 8B",
|
|
"llama3.2 3B",
|
|
"celeb",
|
|
"code-llama",
|
|
"hf_aigcodexmoe",
|
|
"actor",
|
|
"diff_llama",
|
|
"200K",
|
|
"Tool-Calling",
|
|
"tango",
|
|
"Non-Autoregressive",
|
|
"Fake News",
|
|
"Diffusion Transformer",
|
|
"Image Editing",
|
|
"ACE",
|
|
"llama-3.1-instruct-70b",
|
|
"llama-3-instruct-70b",
|
|
"rationality",
|
|
"advanced",
|
|
"southpark",
|
|
"vidore-exclude",
|
|
"covenants",
|
|
"property",
|
|
"deed",
|
|
"racial-covenant",
|
|
"kazakh",
|
|
"pop",
|
|
"hook",
|
|
"music-ai",
|
|
"music-transformer",
|
|
"Trappu/Nemo-Picaro-12B",
|
|
"multi-document",
|
|
"AtAndDev/CapybaraMarcoroni-7B",
|
|
"eren23/DistilHermes-2.5-Mistral-7B",
|
|
"qaic",
|
|
"qaicrt",
|
|
"scientific",
|
|
"serverless",
|
|
"mistral-ft-optimized",
|
|
"neural-hermes",
|
|
"song",
|
|
"Kukedlc/neuronal-7b-Mlab",
|
|
"phonelm",
|
|
"Illusion",
|
|
"eren23/dpo-binarized-NeutrixOmnibe-7B",
|
|
"fourier",
|
|
"task addition",
|
|
"Flare",
|
|
"kl3m",
|
|
"enterprise",
|
|
"jaychou",
|
|
"Lappland the Decadenza",
|
|
"\u8352\u829c\u62c9\u666e\u5170\u5fb7",
|
|
"poses",
|
|
"OpenCoder",
|
|
"Art-Free",
|
|
"upper_sorbian",
|
|
"kannada",
|
|
"diseases",
|
|
"Locutusque/StockQwen-2.5-7B",
|
|
"allknowingroger/QwenSlerp8-7B",
|
|
"full precision",
|
|
"quants",
|
|
"fm4bio",
|
|
"FLUXv1-schnell",
|
|
"Pruned",
|
|
"link",
|
|
"versality",
|
|
"stability",
|
|
"FC",
|
|
"zim-anything",
|
|
"Llama-Doctor",
|
|
"audio-visual",
|
|
"STEM",
|
|
"ChatGLM",
|
|
"real-world",
|
|
"topic-relatedness",
|
|
"semantic-relatedness",
|
|
"GEMM",
|
|
"text_generation",
|
|
"conversation_summarization",
|
|
"dermatology",
|
|
"full-finetune",
|
|
"egyptian",
|
|
"TEST",
|
|
"giux78/zefiro-7b-beta-ITA-v0.1",
|
|
"azale-ai/Starstreak-7b-beta",
|
|
"gagan3012/Mistral_arabic_dpo",
|
|
"davidkim205/komt-mistral-7b-v1",
|
|
"OpenBuddy/openbuddy-zephyr-7b-v14.1",
|
|
"manishiitg/open-aditi-hi-v1",
|
|
"Mixtral 8x7B",
|
|
"Virt-io/Erebus-Holodeck-7B",
|
|
"video depth estimation",
|
|
"wizardmath",
|
|
"mique",
|
|
"Marco-o1",
|
|
"tryon",
|
|
"vto",
|
|
"T3Q-ko-solar-sft-v3.0",
|
|
"kyujinpy/KoCommercial-NoSSL",
|
|
"rqwen",
|
|
"ehristoforu",
|
|
"kphi3",
|
|
"llama_enc",
|
|
"historical person",
|
|
"archival",
|
|
"llava_phi3",
|
|
"fran\u00e7ais",
|
|
"Prompt",
|
|
"foundation_model",
|
|
"MIDI-to-text",
|
|
"MIDI-classification",
|
|
"Style",
|
|
"Isabelia",
|
|
"Character-3D",
|
|
"NFT",
|
|
"mochi-1-preview-diffusers",
|
|
"ShinojiResearch/Senku-70B-Full",
|
|
"cognitivecomputations/TinyDolphin-2.8.2-1.1b-laser",
|
|
"cognitivecomputations/TinyDolphin-2.8.1-1.1b",
|
|
"TinyLlama/TinyLlama-1.1B-intermediate-step-715k-1.5T",
|
|
"SVECTOR",
|
|
"upstage/SOLAR-10.7B-Instruct-v1.0",
|
|
"heavytail/kullm-solar",
|
|
"SOLAR",
|
|
"MathPILE",
|
|
"one-shot",
|
|
"smol",
|
|
"SLERP",
|
|
"pmod_llava_llama",
|
|
"ContaLLM",
|
|
"ContaAI",
|
|
"euclid_qwen2",
|
|
"prompt_enhancement",
|
|
"short_prompt",
|
|
"Prompts",
|
|
"simple-math",
|
|
"v-pred",
|
|
"embedding_space_map",
|
|
"colorization",
|
|
"vaporwave",
|
|
"image_classification",
|
|
"align3r",
|
|
"Unified Medical Language System",
|
|
"National Library of Medicine",
|
|
"umls",
|
|
"aviation",
|
|
"autoround",
|
|
"intel-autoround",
|
|
"woq",
|
|
"intel",
|
|
"long-CoT",
|
|
"Lyra_Qwen2VL_SpeechGenerator",
|
|
"smol-course",
|
|
"module_1",
|
|
"Minecraft",
|
|
"vita-Qwen2",
|
|
"anaphora-resolution",
|
|
"mentions-linking",
|
|
"literary-texts",
|
|
"nested-entities",
|
|
"BookNLP-fr",
|
|
"image2text",
|
|
"camera",
|
|
"Urban Scenario",
|
|
"Synthethic data",
|
|
"RLVR",
|
|
"Extended-Stream",
|
|
"chat-summary",
|
|
"Text classification",
|
|
"Question answering",
|
|
"SER",
|
|
"W4A16",
|
|
"monolithic",
|
|
"wavymulder",
|
|
"luau",
|
|
"roblox",
|
|
"automotive",
|
|
"3D Cartoon",
|
|
"Objects",
|
|
"Game Assets",
|
|
"proximasan",
|
|
"model merge basket",
|
|
"AIGurukul",
|
|
"image_captioning",
|
|
"gguf-node",
|
|
"videorefer_qwen2",
|
|
"erotic",
|
|
"booru",
|
|
"imagebooru",
|
|
"imageboard",
|
|
"gelbooru",
|
|
"guofeng",
|
|
"visual",
|
|
"LID",
|
|
"BERTa",
|
|
"Sarcasm",
|
|
"Egyptian",
|
|
"fill-in-the-blanks",
|
|
"superresolution",
|
|
"pa-IN",
|
|
"Title-Generation",
|
|
"nl_BE",
|
|
"nl_NL",
|
|
"aav",
|
|
"aed",
|
|
"alv",
|
|
"cpf",
|
|
"csg",
|
|
"csn",
|
|
"cus",
|
|
"dra",
|
|
"euq",
|
|
"grk",
|
|
"mkh",
|
|
"nic",
|
|
"pqe",
|
|
"sal",
|
|
"mfs",
|
|
"prl",
|
|
"FewCLUE",
|
|
"4ulan",
|
|
"DPRNNTasNet",
|
|
"DPTNet",
|
|
"VAD",
|
|
"Voice Activity Detection",
|
|
"Openslr Multilingual",
|
|
"Lithuanian",
|
|
"text reranking",
|
|
"botxo",
|
|
"Certainly",
|
|
"sequence classification",
|
|
"Songs",
|
|
"competition",
|
|
"nb-NO",
|
|
"code completion",
|
|
"translation English Spanish model",
|
|
"translation English French model",
|
|
"translation English Swedish model",
|
|
"translation Spanish Cszech model",
|
|
"translation Spanish Deustch model",
|
|
"translation Spanish English model",
|
|
"translation Spanish French model",
|
|
"translation Spanish Italian model",
|
|
"translation Spanish Swedish model",
|
|
"translation Deustch Cszech model",
|
|
"translation French Deustch model",
|
|
"semantic",
|
|
"text Classification",
|
|
"fluency",
|
|
"Conditional Generation",
|
|
"EManuals",
|
|
"customer support",
|
|
"Europarl",
|
|
"reference_recognizer",
|
|
"megatron",
|
|
"license",
|
|
"sentence-classification",
|
|
"scancode",
|
|
"license-compliance",
|
|
"BJP",
|
|
"Congress",
|
|
"AAP",
|
|
"sentence_transformers",
|
|
"bert2bert",
|
|
"BioNLP",
|
|
"topic classification",
|
|
"topic labeling",
|
|
"microsoft/deberta-v3-xsmall",
|
|
"RNN-T",
|
|
"tinybert",
|
|
"loodos-bert-base",
|
|
"CARN",
|
|
"DRLN",
|
|
"MDSR",
|
|
"MSRN",
|
|
"PAN",
|
|
"wmt21",
|
|
"Slovak",
|
|
"f_t5",
|
|
"flax",
|
|
"indonesian-roberta-base",
|
|
"indonesian-roberta-large",
|
|
"diff generation",
|
|
"update summarization",
|
|
"speech to text",
|
|
"sentence-order-prediction",
|
|
"issue",
|
|
"development",
|
|
"rm-sursilv",
|
|
"fastspeech2",
|
|
"google/pegasus-reddit_tifu",
|
|
"glycebert",
|
|
"autobert",
|
|
"rotary position embedding",
|
|
"multimodal-entailment",
|
|
"question-answer generation",
|
|
"polarity",
|
|
"minuscule",
|
|
"bert-large-portuguese-cased",
|
|
"al",
|
|
"ELECTRA",
|
|
"MIT",
|
|
"Dialectal Arabic",
|
|
"metallurgy",
|
|
"spanish gpt2",
|
|
"restaurant",
|
|
"Long documents",
|
|
"bros",
|
|
"SequenceClassification",
|
|
"glpn",
|
|
"deidentification",
|
|
"medical notes",
|
|
"buy-intent",
|
|
"sell-intent",
|
|
"consumer-intent",
|
|
"multitask-model",
|
|
"asr_seq2esq",
|
|
"wikibert",
|
|
"part of speech tagging",
|
|
"semantic textual similarity",
|
|
"sts-ca",
|
|
"tecla",
|
|
"teca",
|
|
"askscience",
|
|
"qarib60_1790k",
|
|
"clinical trial",
|
|
"Universal Sentence Encoder",
|
|
"indonesian-roberta-base-sentiment-classifier",
|
|
"salesken",
|
|
"passage-ranking",
|
|
"neural-search-query-classification",
|
|
"neural-search",
|
|
"autocomplete",
|
|
"Keywords",
|
|
"Keyword Spotting",
|
|
"Command Recognition",
|
|
"question_generation",
|
|
"named-entities",
|
|
"BIO",
|
|
"counterspeech",
|
|
"irt",
|
|
"awesome",
|
|
"cog_view",
|
|
"retribert",
|
|
"vilbert",
|
|
"roberta-wwm",
|
|
"text2text_generation",
|
|
"microscopy",
|
|
"ubertext",
|
|
"Darknet",
|
|
"emoberta",
|
|
"wikibio",
|
|
"MEDIA",
|
|
"shared_bart",
|
|
"bulgarian",
|
|
"macedonian",
|
|
"hate-speech-classification",
|
|
"suicidio",
|
|
"kgqa",
|
|
"STILT",
|
|
"retraining",
|
|
"multi-task learning",
|
|
"anglicisms",
|
|
"loanwords",
|
|
"borrowing",
|
|
"multi_class_classification",
|
|
"crisis",
|
|
"Fake News Detection",
|
|
"QuantizationAwareTraining",
|
|
"eHR",
|
|
"detectron2",
|
|
"/workspace/datasets/datasets/MIR_ST500/MIR_ST500.py",
|
|
"mutlimodal",
|
|
"3DBall",
|
|
"floret",
|
|
"integration",
|
|
"translation evaluation",
|
|
"sentence-summarization",
|
|
"recall",
|
|
"language models",
|
|
"fleurs-asr",
|
|
"speech-enhancement-recognition",
|
|
"geezlab",
|
|
"bertweet",
|
|
"discourse-marker-prediction",
|
|
"pragmatics",
|
|
"discourse",
|
|
"biobert",
|
|
"Indonesian",
|
|
"pix2seq",
|
|
"transfer-learning",
|
|
"covid19",
|
|
"capitalization",
|
|
"forward-looking-statement",
|
|
"text segmentation",
|
|
"deepflash2",
|
|
"ALE/SpaceInvaders-v5",
|
|
"custom-license",
|
|
"auto-complete",
|
|
"generative qa",
|
|
"Taxi-v3-4x4-no_slippery",
|
|
"3D Object Detection",
|
|
"MusicGeneration",
|
|
"hf_diffuse",
|
|
"climate change",
|
|
"gpt-j",
|
|
"gpt-j-6b",
|
|
"data-augmentation",
|
|
"structured-data",
|
|
"tabular-data",
|
|
"arabert",
|
|
"idt5",
|
|
"ldmbert",
|
|
"consistency-regularization",
|
|
"Clinical notes",
|
|
"Discharge summaries",
|
|
"mbert2mbert",
|
|
"face-stylization",
|
|
"Arat5-base",
|
|
"targeted-drug-design",
|
|
"gen_ffa",
|
|
"PyTorch Lightning",
|
|
"Image Translation",
|
|
"binary-classification",
|
|
"seals/CartPole-v0",
|
|
"ML-Agents-Walker",
|
|
"mobilenet_v1",
|
|
"Trinidadian Creole",
|
|
"multiclass-classification",
|
|
"TyDiQA",
|
|
"SQuAD 1.1",
|
|
"text style transfer",
|
|
"graph_nystromformer",
|
|
"covid-19",
|
|
"DialoGPT",
|
|
"ShiftVit",
|
|
"character-level",
|
|
"t5-large-summarization",
|
|
"Video Transformers",
|
|
"medical documents",
|
|
"biomedical papers",
|
|
"MarianNMT",
|
|
"BERTovski",
|
|
"MaltBERTa",
|
|
"hungarian",
|
|
"spoken-language-understanding",
|
|
"Natural Questions List",
|
|
"text summarization",
|
|
"chinese poem",
|
|
"visual-novel",
|
|
"answer-aware-question-generation",
|
|
"image matting",
|
|
"neuspell",
|
|
"spell-correction",
|
|
"factuality",
|
|
"universal",
|
|
"multiset",
|
|
"internet-culture",
|
|
"art_theory",
|
|
"manage",
|
|
"basic_medical_science",
|
|
"pharmacy",
|
|
"public_health",
|
|
"energy_and_power",
|
|
"mechanical_engineering",
|
|
"tool",
|
|
"mindfulness",
|
|
"android-apps",
|
|
"Replete-AI",
|
|
"benchmarks",
|
|
"spatial-reasoning",
|
|
"aspect-based-summarization",
|
|
"simplification-evaluation",
|
|
"word-tokenization",
|
|
"digital-humanities-research",
|
|
"judgement-prediction",
|
|
"compositionality",
|
|
"concepts-to-text",
|
|
"medical-personal-protective-equipment-detection",
|
|
"dialog-act-classification",
|
|
"rationale-extraction",
|
|
"legal-topic-classification",
|
|
"intent-to-text",
|
|
"disambiguation",
|
|
"reddit-posts-summarization",
|
|
"text-search",
|
|
"movielens",
|
|
"dialogue-summary",
|
|
"one-liner-summary",
|
|
"meeting-title",
|
|
"email-subject",
|
|
"named-entity-recognition-and-classification",
|
|
"1800-1900",
|
|
"offensive-language-classification",
|
|
"conversational-question-answering",
|
|
"story-generation",
|
|
"robust-speech-recognition",
|
|
"news, mafand, masakhane",
|
|
"wallstreet",
|
|
"hedgefunds",
|
|
"text-recognition",
|
|
"topics",
|
|
"poems",
|
|
"scholarly text",
|
|
"DAO",
|
|
"legalnlp",
|
|
"class action",
|
|
"dialogue safety",
|
|
"social norm",
|
|
"rules-of-thumb",
|
|
"technical questions",
|
|
"texture-synthesis",
|
|
"non-infringing",
|
|
"doc retrieval",
|
|
"Utilities",
|
|
"Ppe",
|
|
"Assembly Line",
|
|
"Warehouse",
|
|
"Factory",
|
|
"econlp",
|
|
"manufacturing",
|
|
"Transportation",
|
|
"Documents",
|
|
"cross domain",
|
|
"metaphor",
|
|
"figurative language",
|
|
"earth-science",
|
|
"vocabulary",
|
|
"natural-science",
|
|
"comments",
|
|
"forum",
|
|
"flan 2022",
|
|
"flan v2",
|
|
"alexa",
|
|
"Latin",
|
|
"gut-microbiota",
|
|
"project gutenberg",
|
|
"e-book",
|
|
"gutenberg.org",
|
|
"fine-grained ner",
|
|
"multi-humaneval",
|
|
"humaneval",
|
|
"subtitles",
|
|
"Anomaly Detection",
|
|
"common",
|
|
"multi30k",
|
|
"Out Of Distribution",
|
|
"video games",
|
|
"gamedev",
|
|
"databricks",
|
|
"research abstracts",
|
|
"AbeShinzo",
|
|
"FormerJapanesePrimeMinister",
|
|
"applescript",
|
|
"medical consultation",
|
|
"news-topic",
|
|
"masakhanews",
|
|
"masakhane",
|
|
"words",
|
|
"casual",
|
|
"MARC",
|
|
"CommonsenseQA",
|
|
"as2",
|
|
"answer sentence selection",
|
|
"air traffic management",
|
|
"atm",
|
|
"kaggle",
|
|
"scientific paper",
|
|
"atcosim",
|
|
"social science",
|
|
"large language modeling",
|
|
"inverse rendering",
|
|
"material decomposition",
|
|
"atc",
|
|
"deepfakes",
|
|
"LAION",
|
|
"2023",
|
|
"islam",
|
|
"image-text-bounding-box pairs",
|
|
"egypt",
|
|
"text-image-matching",
|
|
"languages",
|
|
"syllable",
|
|
"Affective Captioning",
|
|
"Emotions",
|
|
"commit",
|
|
"patch",
|
|
"self-driving",
|
|
"robotics navigation",
|
|
"semantic segmentation",
|
|
"procedural-generation",
|
|
"Evaluation",
|
|
"answer",
|
|
"customer-support",
|
|
"subset",
|
|
"airoboros",
|
|
"math world problems",
|
|
"Network Security",
|
|
"harm",
|
|
"damage assessment",
|
|
"Podcast",
|
|
"SARFish",
|
|
"Illegal Fishing",
|
|
"Complex-Valued",
|
|
"Synthetic Aperture Radar",
|
|
"Colorectal Pancer",
|
|
"webpages",
|
|
"parlament",
|
|
"fraud-detection",
|
|
"deception-detection",
|
|
"opinion-spam",
|
|
"owl",
|
|
"Persian",
|
|
"religion",
|
|
"storybook",
|
|
"textbook-qa",
|
|
"document-image",
|
|
"explainability",
|
|
"oriented-bounding-boxes",
|
|
"SVG",
|
|
"vector",
|
|
"Robotics",
|
|
"flytech",
|
|
"behavioral",
|
|
"codegeneration",
|
|
"layout-generation",
|
|
"hackernoon",
|
|
"\u65e5\u672c\u8a9e",
|
|
"audio-text",
|
|
"medi",
|
|
"human_feedback",
|
|
"regex",
|
|
"pronunciation-scoring",
|
|
"helpsteer",
|
|
"ai-feedback",
|
|
"visual-chat",
|
|
"multimodal-chat",
|
|
"graphics",
|
|
"Morocco",
|
|
"scene-classification",
|
|
"brain tumor",
|
|
"tumor",
|
|
"instruct-tuning",
|
|
"3D Gaussian Splatting",
|
|
"passports",
|
|
"3D vision",
|
|
"nifty",
|
|
"stock-movement",
|
|
"news-and-events",
|
|
"RLMF",
|
|
"video-summarization",
|
|
"tajik",
|
|
"names",
|
|
"representation learning",
|
|
"Code Efficiency",
|
|
"heritage",
|
|
"novelai",
|
|
"knowledge-graphs",
|
|
"document-type objects",
|
|
"smart contracts",
|
|
"singing voice",
|
|
"entity extraction",
|
|
"natural disasters",
|
|
"MMLU",
|
|
"multi-spectral",
|
|
"SKG",
|
|
"LLM Safety",
|
|
"Multiple Choice",
|
|
"language-learning",
|
|
"caselaw",
|
|
"ICL",
|
|
"patient summary",
|
|
"Forest",
|
|
"children",
|
|
"counseling",
|
|
"breast cancer",
|
|
"coding preferences",
|
|
"llm-as-a-judge",
|
|
"leetcode",
|
|
"automatic_speech_recognition",
|
|
"Caption",
|
|
"technology",
|
|
"simple",
|
|
"\u0641\u0627\u0631\u0633\u06cc",
|
|
"instrument",
|
|
"leyes",
|
|
"peru",
|
|
"constitucion",
|
|
"system prompt",
|
|
"speaker diarization",
|
|
"opus",
|
|
"anthropic",
|
|
"igbo",
|
|
"mediabias",
|
|
"media-bias",
|
|
"product search",
|
|
"Knowledge",
|
|
"3D medical",
|
|
"document-level",
|
|
"toxicity detection",
|
|
"clinical medicine",
|
|
"my little pony",
|
|
"pony preservation project",
|
|
"singing",
|
|
"asl",
|
|
"palestine",
|
|
"CEFR",
|
|
"epigenetics",
|
|
"life sciences",
|
|
"data",
|
|
"disaster",
|
|
"distill",
|
|
"Probability",
|
|
"Liner Algebra",
|
|
"Algebra",
|
|
"Differential Equations",
|
|
"Calculus",
|
|
"over-alignment",
|
|
"freebase",
|
|
"IT",
|
|
"Web Scraping",
|
|
"Media",
|
|
"autonomous_driving",
|
|
"hallucinations",
|
|
"indian",
|
|
"Instruction Tuning",
|
|
"image-to-4d",
|
|
"esoterism",
|
|
"VisualQA",
|
|
"time series analysis",
|
|
"IR",
|
|
"Artificial Intelligence",
|
|
"probability",
|
|
"neuron",
|
|
"posts",
|
|
"information",
|
|
"slot filling",
|
|
"temporal-reasoning",
|
|
"Role-Playing",
|
|
"cti",
|
|
"Small Chunks",
|
|
"Scientific",
|
|
"Scientific Wikipedia",
|
|
"Science Wikipedia",
|
|
"Emotional Intelligence",
|
|
"engineering design",
|
|
"T\u00fcrk\u00e7e",
|
|
"keypoints",
|
|
"pairwise",
|
|
"Information Retrieval",
|
|
"tcm",
|
|
"mscoco",
|
|
"relation-classification",
|
|
"multimodality",
|
|
"photographs",
|
|
"image-data",
|
|
"image-caption pairs",
|
|
"personalization",
|
|
"music images",
|
|
"group",
|
|
"robustness",
|
|
"fstar",
|
|
"popai",
|
|
"fruit",
|
|
"transcript",
|
|
"answers",
|
|
"docker",
|
|
"medieval",
|
|
"constitution",
|
|
"fineweb",
|
|
"time",
|
|
"home-assistant",
|
|
"synthethic",
|
|
"extraction",
|
|
"ibeta",
|
|
"InternVL2",
|
|
"human red teaming",
|
|
"Bioinformatics",
|
|
"truthfulqa",
|
|
"azerbaijan",
|
|
"Human-Language",
|
|
"Customer",
|
|
"MIDI images",
|
|
"MIDI music",
|
|
"tv",
|
|
"aya-23",
|
|
"command-r",
|
|
"cloth",
|
|
"fraud detection",
|
|
"liveness detection",
|
|
"smart meter",
|
|
"Human Caption",
|
|
"Face Caption",
|
|
"surgery",
|
|
"vehicles",
|
|
"cars",
|
|
"ilsvrc-2012",
|
|
"celestia",
|
|
"dicom",
|
|
"cxr",
|
|
"Software",
|
|
"Frameworks",
|
|
"wikimedia",
|
|
"stockfish",
|
|
"event-detection",
|
|
"ARC",
|
|
"ptsd",
|
|
"veterans",
|
|
"buddhism",
|
|
"dharma",
|
|
"exploits",
|
|
"canon",
|
|
"Sports",
|
|
"multi-agent",
|
|
"diverse",
|
|
"Max_length = 8180",
|
|
"truthfulness",
|
|
"debiasing",
|
|
"bias-detection",
|
|
"LLaMA-3.2b",
|
|
"domain-specific",
|
|
"rosbag",
|
|
"ros2",
|
|
"vehicle",
|
|
"canbus",
|
|
"autonomous_vehicles",
|
|
"gesture",
|
|
"fastdata",
|
|
"Gemini",
|
|
"civil engineering",
|
|
"gifteval",
|
|
"logical",
|
|
"DIGIT",
|
|
"slip detection",
|
|
"YOLO11",
|
|
"vqasynth",
|
|
"Dialog",
|
|
"fandom",
|
|
"songs",
|
|
"Ancient Greek",
|
|
"postocr",
|
|
"nom-script",
|
|
"visualization",
|
|
"ir",
|
|
"topic-modeling",
|
|
"context",
|
|
"dialects",
|
|
"overlai.ai",
|
|
"c2pa",
|
|
"contentcredentials",
|
|
"opt-in",
|
|
"podcasts",
|
|
"Prediction",
|
|
"definition",
|
|
"ethical dilemmas",
|
|
"breast-cancer",
|
|
"causal",
|
|
"data-mining",
|
|
"parallel-corpus",
|
|
"ct scans",
|
|
"xray",
|
|
"mammography",
|
|
"radar",
|
|
"formal-methods",
|
|
"coq",
|
|
"fineweb2",
|
|
"sign language",
|
|
"multi-lingual",
|
|
"Indonesion",
|
|
"Bahasa",
|
|
"smart city",
|
|
"genetics",
|
|
"quiz",
|
|
"united-states",
|
|
"real-time",
|
|
"current-events",
|
|
"political-discourse",
|
|
"media-analysis",
|
|
"Gujarati",
|
|
"blogs",
|
|
"adversarial attack",
|
|
"NSFW benchmark",
|
|
"fanfiction",
|
|
"bias-evaluation",
|
|
"dialogue-act-classification",
|
|
"text-to-structured",
|
|
"explanations-in-question-answering",
|
|
"stereotype-detection",
|
|
"synonyms",
|
|
"mobility",
|
|
"auto-generated",
|
|
"other-keyword-spotting",
|
|
"stuctured-to-text",
|
|
"Enzyme Commission",
|
|
"semantic similarity",
|
|
"grug",
|
|
"greentext",
|
|
"code-mixing",
|
|
"mgt",
|
|
"magic-card-game",
|
|
"LAM",
|
|
"middle english",
|
|
"dialogue-response-generation",
|
|
"metaphor-frame-classification",
|
|
"consumer",
|
|
"consumer goods",
|
|
"jobs",
|
|
"yandex",
|
|
"ICD-10",
|
|
"wordnet",
|
|
"quotes",
|
|
"ordinal",
|
|
"cloze",
|
|
"toloka",
|
|
"knowledge base",
|
|
"camera trap data",
|
|
"wildlife monitoring",
|
|
"sentence",
|
|
"ms-coco",
|
|
"gpt-3",
|
|
"bills",
|
|
"semantic-parsing",
|
|
"K-MHaS",
|
|
"Korean NLP",
|
|
"Coling2022",
|
|
"czech NER",
|
|
"riddles",
|
|
"children's speech",
|
|
"icelandic children",
|
|
"icelandic kids",
|
|
"gigafida",
|
|
"samr\u00f3mur",
|
|
"bible",
|
|
"National Corpus of Polish",
|
|
"Narodowy Korpus J\u0119zyka Polskiego",
|
|
"rating prediction",
|
|
"central kurdish",
|
|
"kurdi",
|
|
"fluentui",
|
|
"images ",
|
|
"Aviation",
|
|
"humanitarian",
|
|
"analytical-framework",
|
|
"humset",
|
|
"humbert",
|
|
"instagram",
|
|
"gradio-theme",
|
|
"price",
|
|
"Health",
|
|
"podcast",
|
|
"Relation Classification",
|
|
"Relation extraction",
|
|
"Scientific papers",
|
|
"Research papers",
|
|
"20newsgroups",
|
|
"lam ",
|
|
"model cards",
|
|
"WIP",
|
|
"instructor embeddings",
|
|
"vector stores",
|
|
"comics",
|
|
"duskfallcrew",
|
|
"sentence simplification",
|
|
"document simplification",
|
|
"explainability-judgment-prediction",
|
|
"joke",
|
|
"virtual assistant",
|
|
"compas",
|
|
"ned",
|
|
"mbxp",
|
|
"celebFaces attributes",
|
|
"SugaYoshihide",
|
|
"\u83c5\u7fa9\u5049",
|
|
"consentful",
|
|
"instruction generation",
|
|
"breast",
|
|
"psycholinguistics",
|
|
"Nucleotide",
|
|
"unsupervised",
|
|
"SketchyCOCO",
|
|
"musk",
|
|
"teaser",
|
|
"news snippets",
|
|
"headline generation",
|
|
"teaser generation",
|
|
"keyword generation",
|
|
"tweet generation",
|
|
"news snippet generation",
|
|
"Image Segmentation",
|
|
"hackernews",
|
|
"enriched",
|
|
"cross-lingual",
|
|
"haskell",
|
|
"script",
|
|
"contextual-mt",
|
|
"document-mt",
|
|
"sotu",
|
|
"CN",
|
|
"gpt35-alpha",
|
|
"docugami",
|
|
"dfm-csl",
|
|
"xml-knowledge-graphs",
|
|
"heterogeneous sources",
|
|
"conversational recommendation",
|
|
"Machine Translation",
|
|
"butterfly",
|
|
"dorsal",
|
|
"imbalanced",
|
|
"mimicry",
|
|
"coaching",
|
|
"webcams",
|
|
"indoor",
|
|
"Logistic",
|
|
"Spider",
|
|
"Hello",
|
|
"spider-eval",
|
|
"synthetic speech",
|
|
"Timex",
|
|
"Timexs",
|
|
"Temporal Expression",
|
|
"Temporal Expressions",
|
|
"Temporal Information",
|
|
"Timex Identification",
|
|
"Timex Classification",
|
|
"Timex Extraction",
|
|
"minigpt4",
|
|
"common_sense",
|
|
"political",
|
|
"bundestag",
|
|
"narrated",
|
|
"stars-classification",
|
|
"variant-effect-prediction",
|
|
"jpg",
|
|
"livestream",
|
|
"stream",
|
|
"messages",
|
|
"vtubers",
|
|
"corpora",
|
|
"audioset",
|
|
"fatwa",
|
|
"mufti",
|
|
"cricket",
|
|
"bees",
|
|
"coordinates",
|
|
"geo-tagged",
|
|
"geographic-data",
|
|
"random",
|
|
"single",
|
|
"mixed",
|
|
"Discourse",
|
|
"Discourse Evaluation",
|
|
"brand",
|
|
"comparison",
|
|
"sim-to-real",
|
|
"Bengaluru",
|
|
"disparity maps",
|
|
"depth dataset",
|
|
"ai art",
|
|
"semantic web",
|
|
"dbpedia",
|
|
"NIL",
|
|
"\u5cb8\u7530\u6587\u96c4",
|
|
"KishidaFumio",
|
|
"embryo",
|
|
"acting",
|
|
"source code",
|
|
"code readability",
|
|
"autogen",
|
|
"web-browsing",
|
|
"prodigy",
|
|
"clouds",
|
|
"bank",
|
|
"X",
|
|
"dentistry",
|
|
"radiation protection",
|
|
"EU",
|
|
"Celine",
|
|
"My Theresa",
|
|
"Ounass",
|
|
"tweet-classification",
|
|
"tone",
|
|
"bank-of-ghana",
|
|
"exchange-rates",
|
|
"ghana data",
|
|
"therapy",
|
|
"gender identity",
|
|
"steganography",
|
|
"hpi",
|
|
"workshop",
|
|
"GEITje",
|
|
"cgi",
|
|
"jsonifize",
|
|
"v1.2.1",
|
|
"TimeSeries",
|
|
"CanariaView",
|
|
"CENIA"
|
|
] |