---
title: VoxCPM
canonical_url: "https://www.modelscope.cn/models/AXERA-TECH/VoxCPM"
md_url: "https://www.modelscope.cn/models/AXERA-TECH/VoxCPM.md"
repository: AXERA-TECH/VoxCPM
last_updated: 2026-01-21
license: mit
pipeline_tag: text-to-speech
tasks:
  - text-to-speech
base_model:
  - VoxCPM
base_model_relation: finetune
library_name:
  - onnx
  - pytorch
frameworks:
  - pytorch
language:
  - en
  - zh
downloads: 37
stars: 0
tags:
  - VoxCPM
  - Speech
---

# VoxCPM

> VoxCPM - AXERA-TECH 在 ModelScope 开源的模型。VoxCPM This version of VoxCPM has been converted to run on the Axera NPU using w8a16 quantization. Compatible with Pulsar2 version: 4.2

AXERA-TECH/VoxCPM 是 ModelScope 魔搭社区上的text-to-speech模型，采用 mit 许可，基于 VoxCPM 构建。

- **Repository**: AXERA-TECH/VoxCPM
- **License**: mit
- **Tasks**: text-to-speech
- **Base model**: VoxCPM
- **Tags**: VoxCPM, Speech
- **Downloads**: 37
- **Stars**: 0
- **Last updated**: 2026-01-21

Source: https://www.modelscope.cn/models/AXERA-TECH/VoxCPM

---

# VoxCPM  
This version of VoxCPM has been converted to run on the Axera NPU using **w8a16** quantization.
Compatible with Pulsar2 version: 4.2

## Convert tools links:
For those who are interested in model conversion, you can try to export axmodel through the original repo : 
[VoxCPM offical](https://github.com/OpenBMB/VoxCPM/)

[Pulsar2 Link, How to Convert LLM from Huggingface to axmodel](https://pulsar2-docs.readthedocs.io/en/latest/appendix/build_llm.html) 

[AXera NPU HOST LLM Runtime](https://github.com/AXERA-TECH/VoxCPM.Axera) 

## Support Platform

- AX650
  - AX650N DEMO Board
  - [M4N-Dock(爱芯派Pro)](https://wiki.sipeed.com/hardware/zh/maixIV/m4ndock/m4ndock.html)
  - [M.2 Accelerator card](https://axcl-docs.readthedocs.io/zh-cn/latest/doc_guide_hardware.html)



## How to use

Download all files from this repository to the device  
### 1. Run python demo  

#### 1. Install voxcpm axinfer package  
```
git clone -b 1.0.4-axmode_infer https://github.com/techshoww/VoxCPM.git 
cd VoxCPM
pip3 install .
```

#### 2. Download zipenhancer
```
pip3 install modelscope  
modelscope download --model iic/speech_zipenhancer_ans_multiloss_16k_base --local_dir iic/speech_zipenhancer_ans_multiloss_16k_base
```

#### 3. Run on Axera Device    
Go to the root directory of this project.  run:  
```
python3 run_ax650.py
```

### 2. Run c++ demo  

#### 1. Install transformers
```
pip3 install transformers>=4.56.2
```

#### 2. Start tokenizer server  
```
python3 tokenizer.py --port 9999
```

#### 3. Run c++ demo  
```
bash run_ax650.sh
```