Add Deepseek MoE v1 & GigaChat models #10827
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alterfo
approved these changes
Dec 14, 2024
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@ggerganov Hi! I think this PR is ready, could you check it up? |
ggerganov
approved these changes
Dec 15, 2024
convert_hf_to_gguf.py
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| @Model.register("DeepseekForCausalLM") | ||
| class DeepseekModel(Model): |
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Move before DeepseekV2Model above
src/llama.cpp
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| } | ||
| } | ||
| } break; | ||
| case LLM_ARCH_DEEPSEEK: |
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Move before case LLM_ARCH_DEEPSEEK2 above.
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Thank you for your suggestions! I hadn't noticed that. |
arthw
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Dec 20, 2024
* Add deepseek v1 arch & gigachat template * improve template code * add readme * delete comments * remove comment * fix format * lint llama.cpp * fix order of deepseek and deepseek2, move gigachat temlate to the end of func * fix order of deepseek and deepseek2 in constants; mark shared exp as deepseek arch need * remove comments * move deepseek above deepseek2 * change placement of gigachat chat template
tinglou
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to tinglou/llama.cpp
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Feb 13, 2025
* Add deepseek v1 arch & gigachat template * improve template code * add readme * delete comments * remove comment * fix format * lint llama.cpp * fix order of deepseek and deepseek2, move gigachat temlate to the end of func * fix order of deepseek and deepseek2 in constants; mark shared exp as deepseek arch need * remove comments * move deepseek above deepseek2 * change placement of gigachat chat template
mglambda
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to mglambda/llama.cpp
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Mar 8, 2025
* Add deepseek v1 arch & gigachat template * improve template code * add readme * delete comments * remove comment * fix format * lint llama.cpp * fix order of deepseek and deepseek2, move gigachat temlate to the end of func * fix order of deepseek and deepseek2 in constants; mark shared exp as deepseek arch need * remove comments * move deepseek above deepseek2 * change placement of gigachat chat template
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Self-reported review complexity:
The PR adds support for DeepSeek MoE v1 models (Base and Instruct) & support new GigaChat models (Base and Instruct). Since GigaChat is based on the Deepseek MoE v1 architecture, the changes for that model is limited to the tokenizer.