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@hello-cpaxton hello-cpaxton commented Feb 22, 2025

Description

Adds deepseek as a model option under qwen. Example usage:

python -m stretch.app.chat --llm qwen25-Math-7B-Int4
python -m stretch.app.chat --llm qwen25-0.5B-AWQ
python -m stretch.app.chat --llm qwen25-Coder-7B
python -m stretch.app.chat --llm qwen25-Deepseek-1.5B

Something such as

python -m stretch.app.chat --llm qwen25-Deepseek-3B

should raise error as this is a non existing weight configuration

Note that Deepseek fine tunes aren't all avaialble (i.e., there doesn't seem to be a 3b). So I added bitsandbytes support for quantization, and you can now run Qwen 7b or 14b on ~5 or ~10 gb of vram:

python -m pip install bitsandbytes qwen_vl_utils autoawq transformers>=4.49.0

Checklist

  • I have performed a self-review of my code
  • If it is a core feature, I have added thorough tests
  • I have added documentation for the changes
  • I have updated the README file if necessary
  • I have run on hardware if necessary

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@hello-cpaxton hello-cpaxton self-assigned this Feb 22, 2025
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Based on my search, DeepkSeek R1 only distills Qwen of size 32B, 14B, 7B, and 1.5B

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  • Coder: 32B, 14B, 7B, 3B, 1.5B, 0.5B, (None, Instruct, Instruct-AWQ, Instruct-GGUF, Instruct-GPTQ-Int4, Instruct-GPTQ-Int8)
  • Math: 72B, 7B, 1.5B (None, Instruct)
  • VL: 72B, 7B, 3B (Instruct, Instruct-AWQ)
  • None: "0.5B", "1.5B", "3B", "7B", "14B", "32B", "72B" (None, Instruct, Instruct-AWQ, Instruct-GGUF, Instruct-GPTQ-Int4, Instruct-GPTQ-Int8)
  • Deepseek: 1.5B, 7B, 14B, 32B

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4 participants