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Add Troubleshooting Section to README
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### 6.7 Recommended Inference Functionality with Huawei Ascend NPUs
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### 6.7 Recommended Inference Functionality with Huawei Ascend NPUs
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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).
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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).
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## 7. Troubleshooting
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## 7. License
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### Common Issues and Solutions
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1. **Issue: Model weights not found**
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**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.
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2. **Issue: Inference script fails with a CUDA error**
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**Solution:** Verify the following:
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- The correct version of **CUDA** is installed.
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- GPU drivers are up to date.
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- **PyTorch** is correctly configured to use CUDA.
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For more detailed guidance, refer to the official [PyTorch CUDA Troubleshooting Guide](https://pytorch.org/docs/stable/notes/cuda.html).
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3. **Issue: Slow performance during inference**
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**Solution:** Ensure optimal performance using these tips:
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- Use FP8 or BF16 modes if supported by your hardware (see [How to Run Locally](#6-how-to-run-locally) for setup details).
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- Review [PyTorch Performance Tuning](https://pytorch.org/tutorials/recipes/recipes/tuning_guide.html) for further optimization strategies.
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4. **Issue: Out of memory error**
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**Solution:**
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- Reduce the batch size to fit your GPU memory.
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- Utilize a **model parallelism strategy** to distribute memory usage across multiple GPUs.
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- For multi-GPU setups, consult the [PyTorch Distributed Training Documentation](https://pytorch.org/tutorials/beginner/dist_overview.html).
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### Before Reporting an Issue
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We encourage you to carefully follow the setup and usage instructions provided in this README to ensure proper configuration of DeepSeek-V3.
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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.
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## 8. License
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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.
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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.
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## 8. Citation
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## 9. Citation
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```
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```
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@misc{deepseekai2024deepseekv3technicalreport,
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@misc{deepseekai2024deepseekv3technicalreport,
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title={DeepSeek-V3 Technical Report},
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title={DeepSeek-V3 Technical Report},
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@ -355,5 +386,5 @@ This code repository is licensed under [the MIT License](LICENSE-CODE). The use
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}
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}
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```
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```
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## 9. Contact
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## 10. Contact
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If you have any questions, please raise an issue or contact us at [service@deepseek.com](service@deepseek.com).
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If you have any questions, please raise an issue or contact us at [service@deepseek.com](service@deepseek.com).
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