Instructions to use amanuelbyte/chatterbox-fr-lora-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amanuelbyte/chatterbox-fr-lora-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="amanuelbyte/chatterbox-fr-lora-v2")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("amanuelbyte/chatterbox-fr-lora-v2", device_map="auto") - Chatterbox
How to use amanuelbyte/chatterbox-fr-lora-v2 with Chatterbox:
# pip install chatterbox-tts import torchaudio as ta from chatterbox.tts import ChatterboxTTS model = ChatterboxTTS.from_pretrained(device="cuda") text = "Ezreal and Jinx teamed up with Ahri, Yasuo, and Teemo to take down the enemy's Nexus in an epic late-game pentakill." wav = model.generate(text) ta.save("test-1.wav", wav, model.sr) # If you want to synthesize with a different voice, specify the audio prompt AUDIO_PROMPT_PATH="YOUR_FILE.wav" wav = model.generate(text, audio_prompt_path=AUDIO_PROMPT_PATH) ta.save("test-2.wav", wav, model.sr) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a2901053b7a3a792981219ba227effca256de01473cf3c01e6d0816d705137f
- Size of remote file:
- 7.94 MB
- SHA256:
- 9455e9142dec35ecd3b3a0bde6d1d90a379240bbab96588a9f265f38a46714f9
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