deepseekmirror/DeepSeek-V3
1
0
Fork 0
mirror of https://github.com/deepseek-ai/DeepSeek-V3.git synced 2025-02-22 13:48:56 -05:00
Code Issues Actions 1 Packages Projects Releases Wiki Activity

Add Troubleshooting Section to README

Browse Source
This commit is contained in:
Dhieu 2025-01-28 23:49:43 +03:00
parent b5d872ead0
commit 7e137bb39d
1 changed files with 34 additions and 3 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

37
README.md
View File

@ -338,11 +338,42 @@ In collaboration with the AMD team, we have achieved Day-One support for AMD GPU
### 6.7 Recommended Inference Functionality with Huawei Ascend NPUs
The [MindIE](https://www.hiascend.com/en/software/mindie) framework from the Huawei Ascend community has successfully adapted the BF16 version of DeepSeek-V3. For step-by-step guidance on Ascend NPUs, please follow the [instructions here](https://modelers.cn/models/MindIE/deepseekv3).
## 7. Troubleshooting
## 7. License
### Common Issues and Solutions
1. **Issue: Model weights not found**
**Solution:** Ensure you have downloaded the **DeepSeek-V3 model weights** from [Hugging Face](https://huggingface.co/deepseek-ai/DeepSeek-V3) and placed them in the correct directory as specified in the [How to Run Locally](#6-how-to-run-locally) instructions.
2. **Issue: Inference script fails with a CUDA error**
**Solution:** Verify the following:
- The correct version of **CUDA** is installed.
- GPU drivers are up to date.
- **PyTorch** is correctly configured to use CUDA.
For more detailed guidance, refer to the official [PyTorch CUDA Troubleshooting Guide](https://pytorch.org/docs/stable/notes/cuda.html).
3. **Issue: Slow performance during inference**
**Solution:** Ensure optimal performance using these tips:
- Use FP8 or BF16 modes if supported by your hardware (see [How to Run Locally](#6-how-to-run-locally) for setup details).
- Review [PyTorch Performance Tuning](https://pytorch.org/tutorials/recipes/recipes/tuning_guide.html) for further optimization strategies.
4. **Issue: Out of memory error**
**Solution:**
- Reduce the batch size to fit your GPU memory.
- Utilize a **model parallelism strategy** to distribute memory usage across multiple GPUs.
- For multi-GPU setups, consult the [PyTorch Distributed Training Documentation](https://pytorch.org/tutorials/beginner/dist_overview.html).
### Before Reporting an Issue
We encourage you to carefully follow the setup and usage instructions provided in this README to ensure proper configuration of DeepSeek-V3.
If you encounter any issues not listed in the **Troubleshooting** section, If you have any questions, please raise an issue or contact us at [service@deepseek.com](service@deepseek.com). Be sure to include as much detail as possible about your setup and the problem you're experiencing. This helps us assist you more effectively.
## 8. License
This code repository is licensed under [the MIT License](LICENSE-CODE). The use of DeepSeek-V3 Base/Chat models is subject to [the Model License](LICENSE-MODEL). DeepSeek-V3 series (including Base and Chat) supports commercial use.
## 8. Citation
## 9. Citation
```
@misc{deepseekai2024deepseekv3technicalreport,
title={DeepSeek-V3 Technical Report},
@ -355,5 +386,5 @@ This code repository is licensed under [the MIT License](LICENSE-CODE). The use
}
```
## 9. Contact
## 10. Contact
If you have any questions, please raise an issue or contact us at [service@deepseek.com](service@deepseek.com).