content.raw: What an eventful day in Open Source LLMs today:
content.type: text
content.value: What an eventful day in Open Source LLMs today:
content.type: new_line
content.type: new_line
content.raw: Mistral released Codestral Mamba 🐍
content.type: text
content.value: Mistral released Codestral Mamba 🐍
content.type: new_line
content.raw: > Beats DeepSeek QwenCode, best model < 10B, competitive with Codestral 22B
content.type: text
content.value: > Beats DeepSeek QwenCode, best model < 10B, competitive with Codestral 22B
content.type: new_line
content.raw: > Mamba 2 architecture - supports up to 256K context
content.type: text
content.value: > Mamba 2 architecture - supports up to 256K context
content.type: new_line
content.raw: > Apache 2.0 licensed, perfect for local code assistant
content.type: text
content.value: > Apache 2.0 licensed, perfect for local code assistant
content.type: new_line
content.raw: > Transformers & llama.cpp integration upcoming!
content.type: text
content.value: > Transformers & llama.cpp integration upcoming!
content.type: new_line
content.type: new_line
content.raw: Model checkpoint: 
content.type: text
content.value: Model checkpoint: 
content.href: https://huggingface.co/mistralai/mamba-codestral-7B-v0.1
content.raw: https://huggingface.co/mistralai/mamba-codestral-7B-v0.1
content.type: link
content.type: new_line
content.type: new_line
content.raw: Hugging Face dropped SmolLM 🤏
content.type: text
content.value: Hugging Face dropped SmolLM 🤏
content.type: new_line
content.raw: > Beats MobileLLM, Qwen 0.5B, Phi 1.5B and more!
content.type: text
content.value: > Beats MobileLLM, Qwen 0.5B, Phi 1.5B and more!
content.type: new_line
content.raw: > 135M, 360M, and 1.7B param model checkpoints
content.type: text
content.value: > 135M, 360M, and 1.7B param model checkpoints
content.type: new_line
content.raw: > Trained on 600B high-quality synthetic + FineWeb Edu tokens
content.type: text
content.value: > Trained on 600B high-quality synthetic + FineWeb Edu tokens
content.type: new_line
content.raw: > Architecture: Llama + GQA + 2048 ctx length 
content.type: text
content.value: > Architecture: Llama + GQA + 2048 ctx length 
content.type: new_line
content.raw: > Ripe for fine-tuning and on-device deployments.
content.type: text
content.value: > Ripe for fine-tuning and on-device deployments.
content.type: new_line
content.raw: > Works out of the box with Transformers!
content.type: text
content.value: > Works out of the box with Transformers!
content.type: new_line
content.type: new_line
content.raw: Model checkpoints: 
content.type: text
content.value: Model checkpoints: 
content.raw: https://huggingface.co/collections/HuggingFaceTB/smollm-6695016cad7167254ce15966
content.id: HuggingFaceTB/smollm-6695016cad7167254ce15966
content.type: collection
content.type: resource
content.url: https://huggingface.co/collections/HuggingFaceTB/smollm-6695016cad7167254ce15966
content.type: new_line
content.type: new_line
content.raw: Mistral released Mathstral 7B ∑
content.type: text
content.value: Mistral released Mathstral 7B ∑
content.type: new_line
content.raw: > 56.6% on MATH and 63.47% on MMLU
content.type: text
content.value: > 56.6% on MATH and 63.47% on MMLU
content.type: new_line
content.raw: > Same architecture as Mistral 7B
content.type: text
content.value: > Same architecture as Mistral 7B
content.type: new_line
content.raw: > Works out of the box with Transformers & llama.cpp 
content.type: text
content.value: > Works out of the box with Transformers & llama.cpp 
content.type: new_line
content.raw: > Released under Apache 2.0 license
content.type: text
content.value: > Released under Apache 2.0 license
content.type: new_line
content.type: new_line
content.raw: Model checkpoint: 
content.type: text
content.value: Model checkpoint: 
content.href: https://huggingface.co/mistralai/mathstral-7B-v0.1
content.raw: https://huggingface.co/mistralai/mathstral-7B-v0.1
content.type: link
content.type: new_line
content.type: new_line
content.raw: Pretty dope day for open source ML. Can't wait to see what the community builds with it and to support them further! 🤗
content.type: text
content.value: Pretty dope day for open source ML. Can't wait to see what the community builds with it and to support them further! 🤗
content.type: new_line
content.type: new_line
content.raw: What's your favourite from the release today?
content.type: text
content.value: What's your favourite from the release today?
rawContent: What an eventful day in Open Source LLMs today:
  
  Mistral released Codestral Mamba 🐍
  > Beats DeepSeek QwenCode, best model < 10B, competitive with Codestral 22B
  > Mamba 2 architecture - supports up to 256K context
  > Apache 2.0 licensed, perfect for local code assistant
  > Transformers & llama.cpp integration upcoming!
  
  Model checkpoint: https://huggingface.co/mistralai/mamba-codestral-7B-v0.1
  
  Hugging Face dropped SmolLM 🤏
  > Beats MobileLLM, Qwen 0.5B, Phi 1.5B and more!
  > 135M, 360M, and 1.7B param model checkpoints
  > Trained on 600B high-quality synthetic + FineWeb Edu tokens
  > Architecture: Llama + GQA + 2048 ctx length 
  > Ripe for fine-tuning and on-device deployments.
  > Works out of the box with Transformers!
  
  Model checkpoints: https://huggingface.co/collections/HuggingFaceTB/smollm-6695016cad7167254ce15966
  
  Mistral released Mathstral 7B ∑
  > 56.6% on MATH and 63.47% on MMLU
  > Same architecture as Mistral 7B
  > Works out of the box with Transformers & llama.cpp 
  > Released under Apache 2.0 license
  
  Model checkpoint: https://huggingface.co/mistralai/mathstral-7B-v0.1
  
  Pretty dope day for open source ML. Can't wait to see what the community builds with it and to support them further! 🤗
  
  What's your favourite from the release today?
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commentators._id: 64aea8ff67511bd3d965697b
commentators.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/64aea8ff67511bd3d965697b/Jxn52EmDF5RApJh8antxn.jpeg
commentators.fullname: Feynman Innovations
commentators.name: ajibawa-2023
commentators.type: user