[ "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", 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"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" ]