Instructions to use openbmb/VoxCPM2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- VoxCPM
How to use openbmb/VoxCPM2 with VoxCPM:
import soundfile as sf from voxcpm import VoxCPM model = VoxCPM.from_pretrained("openbmb/VoxCPM2") wav = model.generate( text="VoxCPM is an innovative end-to-end TTS model from ModelBest, designed to generate highly expressive speech.", prompt_wav_path=None, # optional: path to a prompt speech for voice cloning prompt_text=None, # optional: reference text cfg_value=2.0, # LM guidance on LocDiT, higher for better adherence to the prompt, but maybe worse inference_timesteps=10, # LocDiT inference timesteps, higher for better result, lower for fast speed normalize=True, # enable external TN tool denoise=True, # enable external Denoise tool retry_badcase=True, # enable retrying mode for some bad cases (unstoppable) retry_badcase_max_times=3, # maximum retrying times retry_badcase_ratio_threshold=6.0, # maximum length restriction for bad case detection (simple but effective), it could be adjusted for slow pace speech ) sf.write("output.wav", wav, 16000) print("saved: output.wav") - Notebooks
- Google Colab
- Kaggle
cross-lingual transfer without an accent
#14 opened 2 days ago
by
Markobes
Language Support
๐ 1
#11 opened 27 days ago
by
Thangamani
้ณ่ฒ่ฎพ่ฎกไบง็็้ณ้ขๅๆฌก็จไบๅคๅปๆถ็้ฎ้ข
1
#10 opened 29 days ago
by
eldzwdkl
ONNX exports?
#9 opened 30 days ago
by
seedblocks
Thank you to everyone who developed this model.
โค๏ธ 6
#7 opened about 1 month ago
by
abbas78
Decesion
2
#6 opened about 1 month ago
by
Jezecdavins
16-bit quantization
1
#4 opened about 1 month ago
by
semevas
Speed issue in results.
2
#3 opened about 1 month ago
by
Hanswalter
8-bit quantization
๐๐ฅ 4
#2 opened about 1 month ago
by
amarosnithe
ComfyUI Ready ๐
๐๐ 10
1
#1 opened about 1 month ago
by
drbaph