AXERA-TECH/VoxCPM

By AXERA-TECH · ↓ 1 · ♥ 0 · Updated 2025-10-20

What's in this repo

This page lists the files in AXERA-TECH/VoxCPM, including audio_vae.decoder.onnx, audio_vae.encoder.onnx, feat_encoder.in_proj.onnx and more.

4 ONNX models (.onnx files)
98 files, including 50 .axmodel, 8 .bin, 7 .txt, 5 .json, 5 .npy, 4 .onnx
Last updated 2025-10-20

ONNX files

File	Size	Download
axmodels/audio_vae.decoder.onnx	—	Download
axmodels/audio_vae.encoder.onnx	—	Download
axmodels/feat_encoder.in_proj.onnx	—	Download
axmodels/stop_predictor.onnx	—	Download

How to use

These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.

README

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

Pulsar2 Link, How to Convert LLM from Huggingface to axmodel

AXera NPU HOST LLM Runtime

Support Platform

AX650
- AX650N DEMO Board
- M4N-Dock(爱芯派Pro)
- M.2 Accelerator card

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

Model info

text-to-speech transformers

transformers onnx VoxCPM Speech text-to-speech en zh license:mit endpoints_compatible region:us

↓ 1 ♥ 0

Created: 2025-09-30

Updated: 2025-10-20

View on Hugging Face

Files (98)

.gitattributes

README.md

VoxCPM-0.5B/config.json

VoxCPM-0.5B/special_tokens_map.json

VoxCPM-0.5B/tokenizer.json

VoxCPM-0.5B/tokenizer_config.json

assets/en_man1.mp3

assets/en_man1.txt

assets/en_woman1.mp3

assets/en_woman1.txt

assets/zh_man1.txt

assets/zh_man1.wav

assets/zh_man2.mp3

assets/zh_man2.txt

assets/zh_woman1.txt

assets/zh_woman1.wav

axmodels/audio_vae.decoder.onnx ONNX

axmodels/audio_vae.encoder.onnx ONNX

axmodels/enc_to_lm_proj.axmodel

axmodels/feat_encoder.in_proj.axmodel

axmodels/feat_encoder.in_proj.onnx ONNX

axmodels/feat_encoder.special_token.npy

axmodels/feat_encoder.special_token.txt

axmodels/fsq_layer.axmodel

axmodels/lm_to_dit_proj.axmodel

axmodels/locdit.part1.axmodel

axmodels/locdit.part3.axmodel

axmodels/rand_noise.txt

axmodels/res_to_dit_proj.axmodel

axmodels/stop_predictor.axmodel

axmodels/stop_predictor.onnx ONNX

base_lm-axmodels/MiniCPMForCausalLM_p64_l0_together.axmodel

base_lm-axmodels/MiniCPMForCausalLM_p64_l10_together.axmodel

base_lm-axmodels/MiniCPMForCausalLM_p64_l11_together.axmodel

base_lm-axmodels/MiniCPMForCausalLM_p64_l12_together.axmodel

base_lm-axmodels/MiniCPMForCausalLM_p64_l13_together.axmodel

base_lm-axmodels/MiniCPMForCausalLM_p64_l14_together.axmodel

base_lm-axmodels/MiniCPMForCausalLM_p64_l15_together.axmodel

base_lm-axmodels/MiniCPMForCausalLM_p64_l16_together.axmodel

base_lm-axmodels/MiniCPMForCausalLM_p64_l17_together.axmodel

base_lm-axmodels/MiniCPMForCausalLM_p64_l18_together.axmodel

base_lm-axmodels/MiniCPMForCausalLM_p64_l19_together.axmodel

base_lm-axmodels/MiniCPMForCausalLM_p64_l1_together.axmodel

base_lm-axmodels/MiniCPMForCausalLM_p64_l20_together.axmodel

base_lm-axmodels/MiniCPMForCausalLM_p64_l21_together.axmodel

base_lm-axmodels/MiniCPMForCausalLM_p64_l22_together.axmodel

base_lm-axmodels/MiniCPMForCausalLM_p64_l23_together.axmodel

base_lm-axmodels/MiniCPMForCausalLM_p64_l2_together.axmodel

base_lm-axmodels/MiniCPMForCausalLM_p64_l3_together.axmodel

base_lm-axmodels/MiniCPMForCausalLM_p64_l4_together.axmodel

base_lm-axmodels/MiniCPMForCausalLM_p64_l5_together.axmodel

base_lm-axmodels/MiniCPMForCausalLM_p64_l6_together.axmodel

base_lm-axmodels/MiniCPMForCausalLM_p64_l7_together.axmodel

base_lm-axmodels/MiniCPMForCausalLM_p64_l8_together.axmodel

base_lm-axmodels/MiniCPMForCausalLM_p64_l9_together.axmodel

base_lm-axmodels/MiniCPMForCausalLM_post.axmodel

base_lm-axmodels/model.embed_tokens.weight.bfloat16.bin

base_lm-axmodels/model.embed_tokens.weight.float32.bin

base_lm-axmodels/model.embed_tokens.weight.npy

config.json

feat_decoder_estimator_decoder-axmodels/MiniCPMForCausalLM_p5_l0_together.axmodel

feat_decoder_estimator_decoder-axmodels/MiniCPMForCausalLM_p5_l1_together.axmodel

feat_decoder_estimator_decoder-axmodels/MiniCPMForCausalLM_p5_l2_together.axmodel

feat_decoder_estimator_decoder-axmodels/MiniCPMForCausalLM_p5_l3_together.axmodel

feat_decoder_estimator_decoder-axmodels/MiniCPMForCausalLM_post.axmodel

feat_decoder_estimator_decoder-axmodels/model.embed_tokens.weight.bfloat16.bin

feat_decoder_estimator_decoder-axmodels/model.embed_tokens.weight.float32.bin

feat_decoder_estimator_decoder-axmodels/model.embed_tokens.weight.npy

feat_encoder_encoder-axmodels/MiniCPMForCausalLM_p3_l0_together.axmodel

feat_encoder_encoder-axmodels/MiniCPMForCausalLM_p3_l1_together.axmodel

feat_encoder_encoder-axmodels/MiniCPMForCausalLM_p3_l2_together.axmodel

feat_encoder_encoder-axmodels/MiniCPMForCausalLM_p3_l3_together.axmodel

feat_encoder_encoder-axmodels/MiniCPMForCausalLM_post.axmodel

feat_encoder_encoder-axmodels/model.embed_tokens.weight.bfloat16.bin

feat_encoder_encoder-axmodels/model.embed_tokens.weight.float32.bin

feat_encoder_encoder-axmodels/model.embed_tokens.weight.npy

main_ax650

onnxruntime-aarch64-none-gnu-1.16.0/lib/cmake/onnxruntime/onnxruntimeConfig.cmake

onnxruntime-aarch64-none-gnu-1.16.0/lib/cmake/onnxruntime/onnxruntimeConfigVersion.cmake

onnxruntime-aarch64-none-gnu-1.16.0/lib/cmake/onnxruntime/onnxruntimeTargets-release.cmake

onnxruntime-aarch64-none-gnu-1.16.0/lib/cmake/onnxruntime/onnxruntimeTargets.cmake

onnxruntime-aarch64-none-gnu-1.16.0/lib/libonnxruntime.so

onnxruntime-aarch64-none-gnu-1.16.0/lib/libonnxruntime.so.1.16.0

onnxruntime-aarch64-none-gnu-1.16.0/lib/libonnxruntime_providers_shared.so

onnxruntime-aarch64-none-gnu-1.16.0/lib/pkgconfig/libonnxruntime.pc

residual_lm-axmodels/MiniCPMForCausalLM_p64_l0_together.axmodel

residual_lm-axmodels/MiniCPMForCausalLM_p64_l1_together.axmodel

residual_lm-axmodels/MiniCPMForCausalLM_p64_l2_together.axmodel

residual_lm-axmodels/MiniCPMForCausalLM_p64_l3_together.axmodel

residual_lm-axmodels/MiniCPMForCausalLM_p64_l4_together.axmodel

residual_lm-axmodels/MiniCPMForCausalLM_p64_l5_together.axmodel

residual_lm-axmodels/MiniCPMForCausalLM_post.axmodel

residual_lm-axmodels/model.embed_tokens.weight.bfloat16.bin

residual_lm-axmodels/model.embed_tokens.weight.float32.bin

residual_lm-axmodels/model.embed_tokens.weight.npy

run_ax650.py

run_ax650.sh

tokenizer.py

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AXERA-TECH/VoxCPM

What's in this repo

ONNX files

How to use

README

VoxCPM

Convert tools links:

Support Platform

How to use

1. Run python demo

1. Install voxcpm axinfer package

2. Download zipenhancer

3. Run on Axera Device

2. Run c++ demo

1. Install transformers

2. Start tokenizer server

3. Run c++ demo

Model info

Files (98)

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