DeepSeek/DeepSeek-V3
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Merge pull request #21 from eltociear/patch-1

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docs: update README.md
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Huang Panpan 2024-12-30 15:03:30 +08:00 committed by GitHub
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@ -93,12 +93,12 @@ Throughout the entire training process, we did not experience any irrecoverable
| **Model** | **#Total Params** | **#Activated Params** | **Context Length** | **Download** |
| :------------: | :------------: | :------------: | :------------: | :------------: |
| DeepSeek-V3-Base | 671B | 37B | 128K | [🤗 HuggingFace](https://huggingface.co/deepseek-ai/DeepSeek-V3-Base) |
| DeepSeek-V3 | 671B | 37B | 128K | [🤗 HuggingFace](https://huggingface.co/deepseek-ai/DeepSeek-V3) |
| DeepSeek-V3-Base | 671B | 37B | 128K | [🤗 Hugging Face](https://huggingface.co/deepseek-ai/DeepSeek-V3-Base) |
| DeepSeek-V3 | 671B | 37B | 128K | [🤗 Hugging Face](https://huggingface.co/deepseek-ai/DeepSeek-V3) |
</div>
**NOTE: The total size of DeepSeek-V3 models on HuggingFace is 685B, which includes 671B of the Main Model weights and 14B of the Multi-Token Prediction (MTP) Module weights.**
**NOTE: The total size of DeepSeek-V3 models on Hugging Face is 685B, which includes 671B of the Main Model weights and 14B of the Multi-Token Prediction (MTP) Module weights.**
To ensure optimal performance and flexibility, we have partnered with open-source communities and hardware vendors to provide multiple ways to run the model locally. For step-by-step guidance, check out Section 6: [How_to Run_Locally](#6-how-to-run-locally).
@ -243,7 +243,7 @@ cd inference
python fp8_cast_bf16.py --input-fp8-hf-path /path/to/fp8_weights --output-bf16-hf-path /path/to/bf16_weights
```
**NOTE: Huggingface's Transformers has not been directly supported yet.**
**NOTE: Hugging Face's Transformers has not been directly supported yet.**
### 6.1 Inference with DeepSeek-Infer Demo (example only)
@ -262,11 +262,11 @@ cd DeepSeek-V3/inference
pip install -r requirements.txt
```
Download the model weights from HuggingFace, and put them into `/path/to/DeepSeek-V3` folder.
Download the model weights from Hugging Face, and put them into `/path/to/DeepSeek-V3` folder.
#### Model Weights Conversion
Convert HuggingFace model weights to a specific format:
Convert Hugging Face model weights to a specific format:
```shell
python convert.py --hf-ckpt-path /path/to/DeepSeek-V3 --save-path /path/to/DeepSeek-V3-Demo --n-experts 256 --model-parallel 16