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chore(model gallery): add baichuan-inc_baichuan-m2-32 (#6042)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
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- uri: https://huggingface.co/bartowski/BAAI_RoboBrain2.0-7B-GGUF/resolve/main/mmproj-BAAI_RoboBrain2.0-7B-f16.gguf
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sha256: 7c62842afa6b90582acc5758578d5ab683610d33177c9b730f5489404cb28e4f
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filename: mmproj-BAAI_RoboBrain2.0-7B-f16.gguf
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- !!merge <<: *qwen25
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name: "baichuan-inc_baichuan-m2-32b"
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urls:
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- https://huggingface.co/bartowski/baichuan-inc_Baichuan-M2-32B-GGUF
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- https://huggingface.co/baichuan-inc/Baichuan-M2-32B
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description: |
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Baichuan-M2-32B is Baichuan AI's medical-enhanced reasoning model, the second medical model released by Baichuan. Designed for real-world medical reasoning tasks, this model builds upon Qwen2.5-32B with an innovative Large Verifier System. Through domain-specific fine-tuning on real-world medical questions, it achieves breakthrough medical performance while maintaining strong general capabilities.
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Model Features:
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Baichuan-M2 incorporates three core technical innovations: First, through the Large Verifier System, it combines medical scenario characteristics to design a comprehensive medical verification framework, including patient simulators and multi-dimensional verification mechanisms; second, through medical domain adaptation enhancement via Mid-Training, it achieves lightweight and efficient medical domain adaptation while preserving general capabilities; finally, it employs a multi-stage reinforcement learning strategy, decomposing complex RL tasks into hierarchical training stages to progressively enhance the model's medical knowledge, reasoning, and patient interaction capabilities.
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Core Highlights:
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🏆 World's Leading Open-Source Medical Model: Outperforms all open-source models and many proprietary models on HealthBench, achieving medical capabilities closest to GPT-5
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🧠 Doctor-Thinking Alignment: Trained on real clinical cases and patient simulators, with clinical diagnostic thinking and robust patient interaction capabilities
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⚡ Efficient Deployment: Supports 4-bit quantization for single-RTX4090 deployment, with 58.5% higher token throughput in MTP version for single-user scenarios
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overrides:
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parameters:
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model: baichuan-inc_Baichuan-M2-32B-Q4_K_M.gguf
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files:
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- filename: baichuan-inc_Baichuan-M2-32B-Q4_K_M.gguf
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sha256: 51907419518e6f79c28f75e4097518e54c2efecd85cb4c714334395fa2d591c2
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uri: huggingface://bartowski/baichuan-inc_Baichuan-M2-32B-GGUF/baichuan-inc_Baichuan-M2-32B-Q4_K_M.gguf
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- &llama31
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url: "github:mudler/LocalAI/gallery/llama3.1-instruct.yaml@master" ## LLama3.1
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icon: https://avatars.githubusercontent.com/u/153379578
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