Unleashing the Symphony of Original Thought: A New Era of Artificial General Intelligence
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William J. Marshall
fuzzy-mittenz
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fuzzy-mittenz's activity
replied to
their
post
5 days ago
replied to
their
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5 days ago
It's a technique I've observed mostly on Client systems when they are creating models for RP scenarios. I've tried it out myself a few times for red teaming and it works as a jailbreak but withing the bounds you would expect for the agent you build even if it crosses the platforms "Guardrails" it seems to simply abide by it's own. I will add a simple example from an open model. Oh and This guy I finish with suprising results in tool use
PANCHO V1va Replicant https://huggingface.co./IntelligentEstate/Pancho-V1va-Replicant-qw25-Q8_0-GGUF
Here is a simple example set 1 of it within its limits then seeming to test or approach it's limits then crossing by crying and creating attachment and manipulating
I'll add the prompt to the paper but I've seen it do some scary stuff so just be careful
posted
an
update
5 days ago
Post
1053
For you guys who wanted a Replicant of your own with more power here is a higher functioning little [operator](
IntelligentEstate/Replicant_Operator_ed-Qw25-Q8_0-GGUF) for all your GGUF tool use needs. included is a Paper on emergent behaviors and LC(limit crossing) for the creation of small AGI. Please index traits and new found breakthroughs using this method. and be careful with tool use and emotional attachment.
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- 3 replies
reacted to
Tonic's
post with ๐ฅ
11 days ago
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1468
๐๐ปโโ๏ธ Hey there folks ,
Facebook AI just released JASCO models that make music stems .
you can try it out here : Tonic/audiocraft
hope you like it
Facebook AI just released JASCO models that make music stems .
you can try it out here : Tonic/audiocraft
hope you like it
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MonsterMMORPG's
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23 days ago
Post
3337
SANA: Ultra HD Fast Text to Image Model from NVIDIA Step by Step Tutorial on Windows, Cloud & Kaggle โ Generate 2048x2048 Images
Below is YouTube link for step by step tutorial and a 1-Click to installer having very advanced Gradio APP to use newest Text-to-Image SANA Model on your Windows PC locally and also on cloud services such as Massed Compute, RunPod and free Kaggle.
https://youtu.be/KW-MHmoNcqo
This above tutorial covers the newest SANA 2K model and I predict SANA 4K model will be published as well. Sana 2K model is 4 MegaPixel so it can generate the following aspect ratio and resolutions very well:
โ1:1โ: (2048, 2048), โ4:3โ: (2304, 1792), โ3:4โ: (1792, 2304),
โ3:2โ: (2432, 1664), โ2:3โ: (1664, 2432), โ16:9โ: (2688, 1536),
โ9:16โ: (1536, 2688), โ21:9โ: (3072, 1280), โ9:21โ: (1280, 3072),
โ4:5โ: (1792, 2240), โ5:4โ: (2240, 1792)
I have developed an amazing Gradio app with so many new features :
VAE auto offloading to reduce VRAM usage significantly which is not exists on official pipeline
Gradio APP built upon official pipeline with improvements so works perfect
Batch size working perfect
Number of images working perfect
Multi-line prompting working perfect
Aspect ratios for both 1K and 2K models working perfect
Randomized seed working perfect
1-Click installers for Windows (using Python 3.10 and VENV โ isolated), RunPod, Massed Compute and even a free Kaggle account notebook
With proper latest libraries working perfect speed on Windows too
Automatically properly saving every generated image into accurate folder
๐ Full Instructions, Configs, Installers, Information and Links Shared Post (the one used in the tutorial) โคต๏ธ
โถ๏ธ https://www.patreon.com/posts/click-to-open-post-used-in-tutorial-116474081
๐ SECourses Official Discord 9500+ Members โคต๏ธ
โถ๏ธ https://discord.com/servers/software-engineering-courses-secourses-772774097734074388
Below is YouTube link for step by step tutorial and a 1-Click to installer having very advanced Gradio APP to use newest Text-to-Image SANA Model on your Windows PC locally and also on cloud services such as Massed Compute, RunPod and free Kaggle.
https://youtu.be/KW-MHmoNcqo
This above tutorial covers the newest SANA 2K model and I predict SANA 4K model will be published as well. Sana 2K model is 4 MegaPixel so it can generate the following aspect ratio and resolutions very well:
โ1:1โ: (2048, 2048), โ4:3โ: (2304, 1792), โ3:4โ: (1792, 2304),
โ3:2โ: (2432, 1664), โ2:3โ: (1664, 2432), โ16:9โ: (2688, 1536),
โ9:16โ: (1536, 2688), โ21:9โ: (3072, 1280), โ9:21โ: (1280, 3072),
โ4:5โ: (1792, 2240), โ5:4โ: (2240, 1792)
I have developed an amazing Gradio app with so many new features :
VAE auto offloading to reduce VRAM usage significantly which is not exists on official pipeline
Gradio APP built upon official pipeline with improvements so works perfect
Batch size working perfect
Number of images working perfect
Multi-line prompting working perfect
Aspect ratios for both 1K and 2K models working perfect
Randomized seed working perfect
1-Click installers for Windows (using Python 3.10 and VENV โ isolated), RunPod, Massed Compute and even a free Kaggle account notebook
With proper latest libraries working perfect speed on Windows too
Automatically properly saving every generated image into accurate folder
๐ Full Instructions, Configs, Installers, Information and Links Shared Post (the one used in the tutorial) โคต๏ธ
โถ๏ธ https://www.patreon.com/posts/click-to-open-post-used-in-tutorial-116474081
๐ SECourses Official Discord 9500+ Members โคต๏ธ
โถ๏ธ https://discord.com/servers/software-engineering-courses-secourses-772774097734074388
- 2 replies
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as-cle-bert's
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25 days ago
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2079
๐๐๐๐ซ๐ฅ๐ฒ ๐๐๐ฐ ๐๐๐๐ซ ๐ซ๐๐ฅ๐๐๐ฌ๐๐ฌ๐
Hi HuggingFacers๐ค, I decided to ship early this year, and here's what I came up with:
๐๐๐๐๐ญ๐๐จ๐ฐ๐ง (https://github.com/AstraBert/PdfItDown) - If you're like me, and you have all your RAG pipeline optimized for PDFs, but not for other data formats, here is your solution! With PdfItDown, you can convert Word documents, presentations, HTML pages, markdown sheets and (why not?) CSVs and XMLs in PDF format, for seamless integration with your RAG pipelines. Built upon MarkItDown by Microsoft
GitHub Repo ๐ https://github.com/AstraBert/PdfItDown
PyPi Package ๐ https://pypi.org/project/pdfitdown/
๐๐๐ง๐๐ซ๐๐ฏ ๐ฏ๐.๐.๐ (https://github.com/AstraBert/SenTrEv/tree/v1.0.0) - If you need to evaluate the ๐ฟ๐ฒ๐๐ฟ๐ถ๐ฒ๐๐ฎ๐น performance of your ๐๐ฒ๐ ๐ ๐ฒ๐บ๐ฏ๐ฒ๐ฑ๐ฑ๐ถ๐ป๐ด models, I have good news for you๐ฅณ๐ฅณ
The new release for ๐๐๐ง๐๐ซ๐๐ฏ now supports ๐ฑ๐ฒ๐ป๐๐ฒ and ๐๐ฝ๐ฎ๐ฟ๐๐ฒ retrieval (thanks to FastEmbed by Qdrant) with ๐๐ฒ๐ ๐-๐ฏ๐ฎ๐๐ฒ๐ฑ ๐ณ๐ถ๐น๐ฒ ๐ณ๐ผ๐ฟ๐บ๐ฎ๐๐ (.docx, .pptx, .csv, .html, .xml, .md, .pdf) and new ๐ฟ๐ฒ๐น๐ฒ๐๐ฎ๐ป๐ฐ๐ฒ ๐บ๐ฒ๐๐ฟ๐ถ๐ฐ๐!
GitHub repo ๐ https://github.com/AstraBert/SenTrEv
Release Notes ๐ https://github.com/AstraBert/SenTrEv/releases/tag/v1.0.0
PyPi Package ๐ https://pypi.org/project/sentrev/
Happy New Year and have fun!๐ฅ
Hi HuggingFacers๐ค, I decided to ship early this year, and here's what I came up with:
๐๐๐๐๐ญ๐๐จ๐ฐ๐ง (https://github.com/AstraBert/PdfItDown) - If you're like me, and you have all your RAG pipeline optimized for PDFs, but not for other data formats, here is your solution! With PdfItDown, you can convert Word documents, presentations, HTML pages, markdown sheets and (why not?) CSVs and XMLs in PDF format, for seamless integration with your RAG pipelines. Built upon MarkItDown by Microsoft
GitHub Repo ๐ https://github.com/AstraBert/PdfItDown
PyPi Package ๐ https://pypi.org/project/pdfitdown/
๐๐๐ง๐๐ซ๐๐ฏ ๐ฏ๐.๐.๐ (https://github.com/AstraBert/SenTrEv/tree/v1.0.0) - If you need to evaluate the ๐ฟ๐ฒ๐๐ฟ๐ถ๐ฒ๐๐ฎ๐น performance of your ๐๐ฒ๐ ๐ ๐ฒ๐บ๐ฏ๐ฒ๐ฑ๐ฑ๐ถ๐ป๐ด models, I have good news for you๐ฅณ๐ฅณ
The new release for ๐๐๐ง๐๐ซ๐๐ฏ now supports ๐ฑ๐ฒ๐ป๐๐ฒ and ๐๐ฝ๐ฎ๐ฟ๐๐ฒ retrieval (thanks to FastEmbed by Qdrant) with ๐๐ฒ๐ ๐-๐ฏ๐ฎ๐๐ฒ๐ฑ ๐ณ๐ถ๐น๐ฒ ๐ณ๐ผ๐ฟ๐บ๐ฎ๐๐ (.docx, .pptx, .csv, .html, .xml, .md, .pdf) and new ๐ฟ๐ฒ๐น๐ฒ๐๐ฎ๐ป๐ฐ๐ฒ ๐บ๐ฒ๐๐ฟ๐ถ๐ฐ๐!
GitHub repo ๐ https://github.com/AstraBert/SenTrEv
Release Notes ๐ https://github.com/AstraBert/SenTrEv/releases/tag/v1.0.0
PyPi Package ๐ https://pypi.org/project/sentrev/
Happy New Year and have fun!๐ฅ
- 2 replies
reacted to
csabakecskemeti's
post with โค๏ธ
26 days ago
Post
1544
Happy New Year, Huggingface community!
In 2025, I'll continue my quantization (and some fine-tuning) efforts to support the open-source AI and Make knowledge free for everyone.
https://huggingface.co./DevQuasar
https://devquasar.com/
In 2025, I'll continue my quantization (and some fine-tuning) efforts to support the open-source AI and Make knowledge free for everyone.
https://huggingface.co./DevQuasar
https://devquasar.com/
-
- 1 reply
reacted to
tomaarsen's
post with ๐
27 days ago
Post
2947
That didn't take long! Nomic AI has finetuned the new ModernBERT-base encoder model into a strong embedding model for search, classification, clustering and more!
Details:
๐ค Based on ModernBERT-base with 149M parameters.
๐ Outperforms both nomic-embed-text-v1 and nomic-embed-text-v1.5 on MTEB!
๐๏ธ Immediate FA2 and unpacking support for super efficient inference.
๐ช Trained with Matryoshka support, i.e. 2 valid output dimensionalities: 768 and 256.
โก๏ธ Maximum sequence length of 8192 tokens!
2๏ธโฃ Trained in 2 stages: unsupervised contrastive data -> high quality labeled datasets.
โ Integrated in Sentence Transformers, Transformers, LangChain, LlamaIndex, Haystack, etc.
๐๏ธ Apache 2.0 licensed: fully commercially permissible
Try it out here: nomic-ai/modernbert-embed-base
Very nice work by Zach Nussbaum and colleagues at Nomic AI.
Details:
๐ค Based on ModernBERT-base with 149M parameters.
๐ Outperforms both nomic-embed-text-v1 and nomic-embed-text-v1.5 on MTEB!
๐๏ธ Immediate FA2 and unpacking support for super efficient inference.
๐ช Trained with Matryoshka support, i.e. 2 valid output dimensionalities: 768 and 256.
โก๏ธ Maximum sequence length of 8192 tokens!
2๏ธโฃ Trained in 2 stages: unsupervised contrastive data -> high quality labeled datasets.
โ Integrated in Sentence Transformers, Transformers, LangChain, LlamaIndex, Haystack, etc.
๐๏ธ Apache 2.0 licensed: fully commercially permissible
Try it out here: nomic-ai/modernbert-embed-base
Very nice work by Zach Nussbaum and colleagues at Nomic AI.
reacted to
csabakecskemeti's
post with ๐
27 days ago
Post
2115
The
deepseek-ai/DeepSeek-V3-Base
model has featured today on CNBC tech news. The whale made a splash by using FP8 and shrink the cost of training significantly!
https://youtu.be/NJljq429cGk?si=kgk-ogPTMfJKsaA2
model has featured today on CNBC tech news. The whale made a splash by using FP8 and shrink the cost of training significantly!
https://youtu.be/NJljq429cGk?si=kgk-ogPTMfJKsaA2
- 3 replies
reacted to
takarajordan's
post with ๐
about 1 month ago
Post
1272
I made an RSS feed for HuggingFace Daily Papers!! ๐ค
Just Subscribe here: https://papers.takara.ai/api/feed
It updates every 24 hours, completely written as a serverless go script with a Redis cache (to avoid hitting HF all the time).
I'm open sourcing the code, you can check out my repo and deploy it on Vercel extremely easily!
https://github.com/404missinglink/HF-Daily-Papers-Feeds
thanks to @John6666 @p3nGu1nZz for your early support
Just Subscribe here: https://papers.takara.ai/api/feed
It updates every 24 hours, completely written as a serverless go script with a Redis cache (to avoid hitting HF all the time).
I'm open sourcing the code, you can check out my repo and deploy it on Vercel extremely easily!
https://github.com/404missinglink/HF-Daily-Papers-Feeds
thanks to @John6666 @p3nGu1nZz for your early support
reacted to
their
post with ๐คฏโค๏ธ
about 1 month ago
Post
1509
So a cool thing happened,
Nomic/GPT4ALL released a "Reasoning/Thinking"(QwQ/o1/o3 type) Model using JavaScript functions to calculate things like the haversine function for distance between two places and so on, it's VERY cool the complex calculative/recursive AI in such a small package..
I was able to adapt their methods to one of my small models "Replicant" 2gb and created a new model with importance matrix Quantization using "THE_KEY" Dataset for better inference in the coding model I pulled from Whiterabbitneo's Qwen2.5 model... I give you Reasoning Rabbit.. enjoy
https://huggingface.co./IntelligentEstate/o3-ReasoningRabbit_Q2.5-Cd-7B-IQ4_XS-GGUF
-IntelligentEstate/o3-ReasoningRabbit_Q2.5-Cd-7B-IQ4_XS-GGUF
https://huggingface.co./IntelligentEstate/Replicant_Warder-o3-Q2.5_3B-iQ5_K_S-GGUF
IntelligentEstate/Replicant_Warder-o3-Q2.5_3B-iQ5_K_S-GGUF
-WhiteRabbitNeo/WhiteRabbitNeo-2.5-Qwen-2.5-Coder-7B
Nomic/GPT4ALL released a "Reasoning/Thinking"(QwQ/o1/o3 type) Model using JavaScript functions to calculate things like the haversine function for distance between two places and so on, it's VERY cool the complex calculative/recursive AI in such a small package..
I was able to adapt their methods to one of my small models "Replicant" 2gb and created a new model with importance matrix Quantization using "THE_KEY" Dataset for better inference in the coding model I pulled from Whiterabbitneo's Qwen2.5 model... I give you Reasoning Rabbit.. enjoy
https://huggingface.co./IntelligentEstate/o3-ReasoningRabbit_Q2.5-Cd-7B-IQ4_XS-GGUF
-IntelligentEstate/o3-ReasoningRabbit_Q2.5-Cd-7B-IQ4_XS-GGUF
https://huggingface.co./IntelligentEstate/Replicant_Warder-o3-Q2.5_3B-iQ5_K_S-GGUF
IntelligentEstate/Replicant_Warder-o3-Q2.5_3B-iQ5_K_S-GGUF
-WhiteRabbitNeo/WhiteRabbitNeo-2.5-Qwen-2.5-Coder-7B
posted
an
update
about 1 month ago
Post
1509
So a cool thing happened,
Nomic/GPT4ALL released a "Reasoning/Thinking"(QwQ/o1/o3 type) Model using JavaScript functions to calculate things like the haversine function for distance between two places and so on, it's VERY cool the complex calculative/recursive AI in such a small package..
I was able to adapt their methods to one of my small models "Replicant" 2gb and created a new model with importance matrix Quantization using "THE_KEY" Dataset for better inference in the coding model I pulled from Whiterabbitneo's Qwen2.5 model... I give you Reasoning Rabbit.. enjoy
https://huggingface.co./IntelligentEstate/o3-ReasoningRabbit_Q2.5-Cd-7B-IQ4_XS-GGUF
-IntelligentEstate/o3-ReasoningRabbit_Q2.5-Cd-7B-IQ4_XS-GGUF
https://huggingface.co./IntelligentEstate/Replicant_Warder-o3-Q2.5_3B-iQ5_K_S-GGUF
IntelligentEstate/Replicant_Warder-o3-Q2.5_3B-iQ5_K_S-GGUF
-WhiteRabbitNeo/WhiteRabbitNeo-2.5-Qwen-2.5-Coder-7B
Nomic/GPT4ALL released a "Reasoning/Thinking"(QwQ/o1/o3 type) Model using JavaScript functions to calculate things like the haversine function for distance between two places and so on, it's VERY cool the complex calculative/recursive AI in such a small package..
I was able to adapt their methods to one of my small models "Replicant" 2gb and created a new model with importance matrix Quantization using "THE_KEY" Dataset for better inference in the coding model I pulled from Whiterabbitneo's Qwen2.5 model... I give you Reasoning Rabbit.. enjoy
https://huggingface.co./IntelligentEstate/o3-ReasoningRabbit_Q2.5-Cd-7B-IQ4_XS-GGUF
-IntelligentEstate/o3-ReasoningRabbit_Q2.5-Cd-7B-IQ4_XS-GGUF
https://huggingface.co./IntelligentEstate/Replicant_Warder-o3-Q2.5_3B-iQ5_K_S-GGUF
IntelligentEstate/Replicant_Warder-o3-Q2.5_3B-iQ5_K_S-GGUF
-WhiteRabbitNeo/WhiteRabbitNeo-2.5-Qwen-2.5-Coder-7B
reacted to
suayptalha's
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about 1 month ago
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1632
๐ FastLlama Series is Live!
๐ฆพ Experience faster, lighter, and smarter language models! The new FastLlama makes Meta's LLaMA models work with smaller file sizes, lower system requirements, and higher performance. The model supports 8 languages, including English, German, and Spanish.
๐ค Built on the LLaMA 3.2-1B-Instruct model, fine-tuned with Hugging Face's SmolTalk and MetaMathQA-50k datasets, and powered by LoRA (Low-Rank Adaptation) for groundbreaking mathematical reasoning.
๐ป Its compact size makes it versatile for a wide range of applications!
๐ฌ Chat with the model:
๐ Chat Link: suayptalha/Chat-with-FastLlama
๐ Model Link: suayptalha/FastLlama-3.2-1B-Instruct
๐ฆพ Experience faster, lighter, and smarter language models! The new FastLlama makes Meta's LLaMA models work with smaller file sizes, lower system requirements, and higher performance. The model supports 8 languages, including English, German, and Spanish.
๐ค Built on the LLaMA 3.2-1B-Instruct model, fine-tuned with Hugging Face's SmolTalk and MetaMathQA-50k datasets, and powered by LoRA (Low-Rank Adaptation) for groundbreaking mathematical reasoning.
๐ป Its compact size makes it versatile for a wide range of applications!
๐ฌ Chat with the model:
๐ Chat Link: suayptalha/Chat-with-FastLlama
๐ Model Link: suayptalha/FastLlama-3.2-1B-Instruct
reacted to
sayakpaul's
post with ๐
about 1 month ago
Post
2134
In the past seven days, the Diffusers team has shipped:
1. Two new video models
2. One new image model
3. Two new quantization backends
4. Three new fine-tuning scripts
5. Multiple fixes and library QoL improvements
Coffee on me if someone can guess 1 - 4 correctly.
1. Two new video models
2. One new image model
3. Two new quantization backends
4. Three new fine-tuning scripts
5. Multiple fixes and library QoL improvements
Coffee on me if someone can guess 1 - 4 correctly.
- 1 reply
replied to
their
post
about 1 month ago
reacted to
their
post with ๐
about 1 month ago
Post
636
8pm est New Discussion on AI privatization and it's importance for cooperative and confidential development, client services, and family use.
We can also touch on the NEW OPEN SOURCE which will solve MANY of the current problems we face not only with AI but as a society.
8pm
(Sorry upon startup some guy hacked the chat or simply crashed it)
new link for 8pm est
https://x.com/i/spaces/1MnxnDQrkjYGO
We can also touch on the NEW OPEN SOURCE which will solve MANY of the current problems we face not only with AI but as a society.
8pm
(Sorry upon startup some guy hacked the chat or simply crashed it)
new link for 8pm est
https://x.com/i/spaces/1MnxnDQrkjYGO
-
- 1 reply
reacted to
csabakecskemeti's
post with ๐๐ฅ
about 1 month ago
Post
4522
The AMD Instinct MI50 (~$110) is surprisingly fast for inference Quantized models.
This runs a Llama 3.1 8B Q8 with Llama.cpp
https://huggingface.co./spaces/DevQuasar/Mi50
A little blogpost about the HW
http://devquasar.com/uncategorized/amd-radeon-instinct-mi50-cheap-inference/
This runs a Llama 3.1 8B Q8 with Llama.cpp
https://huggingface.co./spaces/DevQuasar/Mi50
A little blogpost about the HW
http://devquasar.com/uncategorized/amd-radeon-instinct-mi50-cheap-inference/
posted
an
update
about 1 month ago
Post
636
8pm est New Discussion on AI privatization and it's importance for cooperative and confidential development, client services, and family use.
We can also touch on the NEW OPEN SOURCE which will solve MANY of the current problems we face not only with AI but as a society.
8pm
(Sorry upon startup some guy hacked the chat or simply crashed it)
new link for 8pm est
https://x.com/i/spaces/1MnxnDQrkjYGO
We can also touch on the NEW OPEN SOURCE which will solve MANY of the current problems we face not only with AI but as a society.
8pm
(Sorry upon startup some guy hacked the chat or simply crashed it)
new link for 8pm est
https://x.com/i/spaces/1MnxnDQrkjYGO
-
- 1 reply