Instructions to use AXERA-TECH/VoxCPM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AXERA-TECH/VoxCPM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="AXERA-TECH/VoxCPM")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AXERA-TECH/VoxCPM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download feat_encoder_encoder-axmodels/MiniCPMForCausalLM_post.axmodel from AXERA-TECH/VoxCPM: direct link, hf CLI and curl.
- Browser
- Download file 37.6 kB
-
https://huggingface.co/AXERA-TECH/VoxCPM/resolve/main/feat_encoder_encoder-axmodels/MiniCPMForCausalLM_post.axmodel
- Command line
-
hf download hf://AXERA-TECH/VoxCPM/feat_encoder_encoder-axmodels/MiniCPMForCausalLM_post.axmodel
-
curl -L -o MiniCPMForCausalLM_post.axmodel https://huggingface.co/AXERA-TECH/VoxCPM/resolve/main/feat_encoder_encoder-axmodels/MiniCPMForCausalLM_post.axmodel
37.6 kB
- Xet hash:
- b7368aad2c22a0b968c65fcaecbdfa6ff7ce1c4f8e2ef205991e10482d156fac
- Size of remote file:
- 37.6 kB
- SHA256:
- d51ee039826ff233cae480c5d3562bc65058d2fe3649dc0660b8411337648182
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