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--- |
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license: mit |
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language: |
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- en |
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- zh |
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base_model: |
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- VoxCPM |
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pipeline_tag: text-to-speech |
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library_name: transformers |
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tags: |
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- VoxCPM |
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- Speech |
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--- |
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# VoxCPM |
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This version of VoxCPM has been converted to run on the Axera NPU using **w8a16** quantization. |
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Compatible with Pulsar2 version: 4.2 |
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## Convert tools links: |
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For those who are interested in model conversion, you can try to export axmodel through the original repo : |
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[VoxCPM offical](https://github.com/OpenBMB/VoxCPM/) |
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[Pulsar2 Link, How to Convert LLM from Huggingface to axmodel](https://pulsar2-docs.readthedocs.io/en/latest/appendix/build_llm.html) |
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[AXera NPU HOST LLM Runtime](https://github.com/AXERA-TECH/VoxCPM.Axera) |
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## Support Platform |
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- AX650 |
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- AX650N DEMO Board |
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- [M4N-Dock(爱芯派Pro)](https://wiki.sipeed.com/hardware/zh/maixIV/m4ndock/m4ndock.html) |
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- [M.2 Accelerator card](https://axcl-docs.readthedocs.io/zh-cn/latest/doc_guide_hardware.html) |
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## How to use |
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Download all files from this repository to the device |
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### 1. Run python demo |
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#### 1. Install voxcpm axinfer package |
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``` |
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git clone -b 1.0.4-axmode_infer https://github.com/techshoww/VoxCPM.git |
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cd VoxCPM |
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pip3 install . |
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``` |
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#### 2. Download zipenhancer |
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``` |
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pip3 install modelscope |
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modelscope download --model iic/speech_zipenhancer_ans_multiloss_16k_base --local_dir iic/speech_zipenhancer_ans_multiloss_16k_base |
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``` |
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#### 3. Run on Axera Device |
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Go to the root directory of this project. run: |
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``` |
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python3 run_ax650.py |
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``` |
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### 2. Run c++ demo |
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#### 1. Install transformers |
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``` |
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pip3 install transformers>=4.56.2 |
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``` |
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#### 2. Start tokenizer server |
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``` |
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python3 tokenizer.py --port 9999 |
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``` |
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#### 3. Run c++ demo |
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``` |
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bash run_ax650.sh |
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``` |
