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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reacted to
Tonic's
post with ๐ฅ
about 20 hours ago
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1130
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
reacted to
MonsterMMORPG's
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14 days ago
Post
3327
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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16 days ago
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2071
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
16 days ago
Post
1540
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
17 days ago
Post
2815
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
18 days ago
Post
2112
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
24 days ago
Post
1209
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 ๐คฏ
24 days ago
Post
1478
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
their
post with โค๏ธ
26 days ago
Post
1478
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
26 days ago
Post
1478
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
post with โค๏ธ
29 days ago
Post
1630
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
1953
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
625
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
4509
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
625
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
freddyaboulton's
post with ๐
about 1 month ago
Post
1557
Hello Llama 3.2! ๐ฃ๏ธ๐ฆ
Build a Siri-like coding assistant that responds to "Hello Llama" in 100 lines of python! All with Gradio, webRTC ๐
freddyaboulton/hey-llama-code-editor
Build a Siri-like coding assistant that responds to "Hello Llama" in 100 lines of python! All with Gradio, webRTC ๐
freddyaboulton/hey-llama-code-editor
reacted to
takarajordan's
post with ๐
about 1 month ago
Post
2297
I'm super excited to release my first open-source text dataset:
WorldScenario 20K is a novel dataset of 20,000 synthetically generated multi-stakeholder scenarios designed to simulate real-world decision-making processes. Each scenario explores a unique environmental, societal, or economic issue.
I used the brand new meta-llama/Llama-3.3-70B-Instruct model to generate this dataset and I put the dataset through some post processing to clean and evaluate the dataset for diversity.
I'd appreciate some feedback and thoughts on my new release! Thanks!
takarajordan/WorldScenario_20K
WorldScenario 20K is a novel dataset of 20,000 synthetically generated multi-stakeholder scenarios designed to simulate real-world decision-making processes. Each scenario explores a unique environmental, societal, or economic issue.
I used the brand new meta-llama/Llama-3.3-70B-Instruct model to generate this dataset and I put the dataset through some post processing to clean and evaluate the dataset for diversity.
I'd appreciate some feedback and thoughts on my new release! Thanks!
takarajordan/WorldScenario_20K
-
- 8 replies
reacted to
burtenshaw's
post with ๐
about 1 month ago
Post
2666
For anyone looking to boost their LLM fine-tuning and alignment skills this decemeber. We're running this free and open course called smol course. Itโs not big like Li Yin and
@mlabonne
, itโs just smol.
๐ท It focuses on practical use cases, so if youโre working on something, bring it along.
๐ฏโโ๏ธ Itโs peer reviewed and open so you can discuss and get feedback.
๐ค If youโre already a smol pro, feel free to drop a star or issue.
> > Part 1 starts now, and itโs on instruction tuning!
https://github.com/huggingface/smol-course
๐ท It focuses on practical use cases, so if youโre working on something, bring it along.
๐ฏโโ๏ธ Itโs peer reviewed and open so you can discuss and get feedback.
๐ค If youโre already a smol pro, feel free to drop a star or issue.
> > Part 1 starts now, and itโs on instruction tuning!
https://github.com/huggingface/smol-course