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Diaries of Open Source. Part 4!
Diaries of Open Source. Part 4!
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🌏Cohere and Cohere4AI release Command-R, a 35B model that is multilingual, RAG-optimized, and can manage tools!
🌏Cohere and Cohere4AI release Command-R, a 35B model that is multilingual, RAG-optimized, and can manage tools!
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Model: 
Model: 
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https://huggingface.co/CohereForAI/c4ai-command-r-v01
model
CohereForAI/c4ai-command-r-v01
https://huggingface.co/CohereForAI/c4ai-command-r-v01
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Blog post: 
Blog post: 
link
https://txt.cohere.com/command-r/
https://txt.cohere.com/command-r/
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🧑‍🍳StarChat2: A powerful code model that is conversational 
🧑‍🍳StarChat2: A powerful code model that is conversational 
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Try it out: 
Try it out: 
resource
https://huggingface.co/spaces/HuggingFaceH4/starchat2-playground
space
HuggingFaceH4/starchat2-playground
https://huggingface.co/spaces/HuggingFaceH4/starchat2-playground
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Repos: 
Repos: 
resource
https://huggingface.co/collections/HuggingFaceH4/starchat2-15b-65f068417b330fafad751fce
collection
HuggingFaceH4/starchat2-15b-65f068417b330fafad751fce
https://huggingface.co/collections/HuggingFaceH4/starchat2-15b-65f068417b330fafad751fce
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Training code: 
Training code: 
link
https://github.com/huggingface/alignment-handbook/tree/main/recipes/starchat2-15b
https://github.com/huggingface/alignment-handbook/tree/main/recipes/starchat2-15b
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🐲Yi-9B: trained on 3 trillion tokens, this english-chinese LLM is quite good and with a very nice detailed report!
🐲Yi-9B: trained on 3 trillion tokens, this english-chinese LLM is quite good and with a very nice detailed report!
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Model: 
Model: 
resource
https://huggingface.co/01-ai/Yi-9B
model
01-ai/Yi-9B
https://huggingface.co/01-ai/Yi-9B
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Paper: 
Paper: 
resource
https://huggingface.co/papers/2403.04652
paper
2403.04652
https://huggingface.co/papers/2403.04652
Yi: Open Foundation Models by 01.AI (2403.04652)
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🐋DeepSeek-VL, 1.3B and 7B VLMs
🐋DeepSeek-VL, 1.3B and 7B VLMs
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Paper: 
Paper: 
resource
https://hf.co/papers/2403.05525
paper
2403.05525
https://hf.co/papers/2403.05525
DeepSeek-VL: Towards Real-World Vision-Language Understanding (2403.05525)
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Large model: 
Large model: 
resource
https://huggingface.co/deepseek-ai/deepseek-vl-7b-chat
model
deepseek-ai/deepseek-vl-7b-chat
https://huggingface.co/deepseek-ai/deepseek-vl-7b-chat
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✍️Writer releases OmniACT: a dataset for multimodal agents for desktop and web.
✍️Writer releases OmniACT: a dataset for multimodal agents for desktop and web.
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Dataset: 
Dataset: 
resource
https://huggingface.co/datasets/Writer/omniact
dataset
Writer/omniact
https://huggingface.co/datasets/Writer/omniact
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Paper: 
Paper: 
resource
https://huggingface.co/papers/2402.17553
paper
2402.17553
https://huggingface.co/papers/2402.17553
OmniACT: A Dataset and Benchmark for Enabling Multimodal Generalist
  Autonomous Agents for Desktop and Web (2402.17553)
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🍎Apple releases MobileCLIP: fast image-text models! 
🍎Apple releases MobileCLIP: fast image-text models! 
link
https://github.com/apple/ml-mobileclip
https://github.com/apple/ml-mobileclip
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🦙💪LlamaGym - fine-tune LLM agents with RL in just a few lines of code! 
🦙💪LlamaGym - fine-tune LLM agents with RL in just a few lines of code! 
link
https://github.com/KhoomeiK/LlamaGym
https://github.com/KhoomeiK/LlamaGym
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 🖼️New multimodal leaderboard ConTextual 
 🖼️New multimodal leaderboard ConTextual 
link
https://huggingface.co/blog/leaderboard-contextual
https://huggingface.co/blog/leaderboard-contextual
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🎁 Design2Code: benchmark for multimodal LLMs for automating front-end development. 
🎁 Design2Code: benchmark for multimodal LLMs for automating front-end development. 
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Dataset 
Dataset 
resource
https://huggingface.co/datasets/SALT-NLP/Design2Code
dataset
SALT-NLP/Design2Code
https://huggingface.co/datasets/SALT-NLP/Design2Code
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Paper 
Paper 
resource
https://huggingface.co/papers/2403.03163
paper
2403.03163
https://huggingface.co/papers/2403.03163
Design2Code: How Far Are We From Automating Front-End Engineering? (2403.03163)
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Project 
Project 
link
https://salt-nlp.github.io/Design2Code/
https://salt-nlp.github.io/Design2Code/
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You can find the previous part at 
You can find the previous part at 
link
https://huggingface.co/posts/osanseviero/633758457910104
https://huggingface.co/posts/osanseviero/633758457910104
Diaries of Open Source. Part 4!

🌏Cohere and Cohere4AI release Command-R, a 35B model that is multilingual, RAG-optimized, and can manage tools!
Model: https://huggingface.co/CohereForAI/c4ai-command-r-v01
Blog post: https://txt.cohere.com/command-r/

🧑‍🍳StarChat2: A powerful code model that is conversational 
Try it out: https://huggingface.co/spaces/HuggingFaceH4/starchat2-playground
Repos: https://huggingface.co/collections/HuggingFaceH4/starchat2-15b-65f068417b330fafad751fce
Training code: https://github.com/huggingface/alignment-handbook/tree/main/recipes/starchat2-15b

🐲Yi-9B: trained on 3 trillion tokens, this english-chinese LLM is quite good and with a very nice detailed report!
Model: https://huggingface.co/01-ai/Yi-9B
Paper: https://huggingface.co/papers/2403.04652

🐋DeepSeek-VL, 1.3B and 7B VLMs
Paper: https://hf.co/papers/2403.05525
Large model: https://huggingface.co/deepseek-ai/deepseek-vl-7b-chat

✍️Writer releases OmniACT: a dataset for multimodal agents for desktop and web.
Dataset: https://huggingface.co/datasets/Writer/omniact
Paper: https://huggingface.co/papers/2402.17553

🍎Apple releases MobileCLIP: fast image-text models! https://github.com/apple/ml-mobileclip

🦙💪LlamaGym - fine-tune LLM agents with RL in just a few lines of code! https://github.com/KhoomeiK/LlamaGym 

 🖼️New multimodal leaderboard ConTextual https://huggingface.co/blog/leaderboard-contextual

🎁 Design2Code: benchmark for multimodal LLMs for automating front-end development. 
Dataset https://huggingface.co/datasets/SALT-NLP/Design2Code
Paper https://huggingface.co/papers/2403.03163
Project https://salt-nlp.github.io/Design2Code/

You can find the previous part at https://huggingface.co/posts/osanseviero/633758457910104
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