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license: llama3.1
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# π Introduction
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Data: We collected and cleaned high-quality medical knowledge data. With the help of commercial large models, we expanded the training set to about 8,000 high-quality instruction samples, covering key medical subfields such as treatment and pharmacology.
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Framework: DeepSpeed
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If you are interested in technologies such as DeepSpeed distributed training, LoRA fine-tuning, VLLM-based high-concurrency inference service deployment, or model quantization
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license: llama3.1
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language:
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- zh
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metrics:
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- bleu
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pipeline_tag: question-answering
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# π Introduction
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Data: We collected and cleaned high-quality medical knowledge data. With the help of commercial large models, we expanded the training set to about 8,000 high-quality instruction samples, covering key medical subfields such as treatment and pharmacology.
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Framework: [DeepSpeed](https://github.com/deepspeedai/DeepSpeed)
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If you are interested in technologies such as DeepSpeed distributed training, LoRA fine-tuning, VLLM-based high-concurrency inference service deployment, or model quantization, feel free to check out my [open-source project](https://github.com/RyanZxucheng/deepspeed-sft), provided for everyone to learn from.
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