[Doc][Build] Update build doc and faq (#568)

Update build doc and faq about deepseek w8a8

Signed-off-by: MengqingCao <cmq0113@163.com>
This commit is contained in:
Mengqing Cao
2025-04-18 14:16:41 +08:00
committed by GitHub
parent e66ded5679
commit b91f9a5afd
2 changed files with 3 additions and 5 deletions

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@@ -84,11 +84,9 @@ Currently, there is no quantization method supported in vllm-ascend originally.
### 11. How to run w8a8 DeepSeek model?
Currently, running on v0.7.3, we should run w8a8 with vllm + vllm-ascend + mindie-turbo. And we only need vllm + vllm-ascend when v0.8.X is released. After installing the above packages, you can follow the steps below to run w8a8 DeepSeek:
Currently, w8a8 DeepSeek is working in process: [support AscendW8A8 quantization](https://github.com/vllm-project/vllm-ascend/pull/511)
1. Quantize bf16 DeepSeek, e.g. [unsloth/DeepSeek-R1-BF16](https://modelscope.cn/models/unsloth/DeepSeek-R1-BF16), with msModelSlim to get w8a8 DeepSeek. Find more details in [msModelSlim doc](https://gitee.com/ascend/msit/tree/master/msmodelslim/msmodelslim/pytorch/llm_ptq)
2. Copy the content of `quant_model_description_w8a8_dynamic.json` into the `quantization_config` of `config.json` of the quantized model files.
3. Reference with the quantized DeepSeek model.
Please run DeepSeek with BF16 now, follwing the [Multi-Node DeepSeek inferencing tutorail](https://vllm-ascend.readthedocs.io/en/main/tutorials/multi_node.html)
### 12. There is not output in log when loading models using vllm-ascend, How to solve it?

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@@ -78,7 +78,7 @@ python -m venv vllm-ascend-env
source vllm-ascend-env/bin/activate
# Install required python packages.
pip3 install -i https://pypi.tuna.tsinghua.edu.cn/simple attrs numpy<2.0.0 decorator sympy cffi pyyaml pathlib2 psutil protobuf scipy requests absl-py wheel typing_extensions
pip3 install -i https://pypi.tuna.tsinghua.edu.cn/simple attrs 'numpy<2.0.0' decorator sympy cffi pyyaml pathlib2 psutil protobuf scipy requests absl-py wheel typing_extensions
# Download and install the CANN package.
wget https://ascend-repo.obs.cn-east-2.myhuaweicloud.com/CANN/CANN%208.0.0/Ascend-cann-toolkit_8.0.0_linux-aarch64.run