Instructions to use Imbatmann/chatterbox-nepali-finetuned-quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Chatterbox
How to use Imbatmann/chatterbox-nepali-finetuned-quantized 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
Chatterbox Nepali Finetuned (FP16 Quantized)
This repository contains FP16 quantized weights for a Nepali fine-tuned Chatterbox TTS setup.
Included files
t3_mtl23ls_v2.safetensorss3gen.ptve.ptCangjie5_TC.jsongrapheme_mtl_merged_expanded_v1.json
Notes
- Intended for Nepali (
ne) text-to-speech workflows based on Chatterbox. - Model artifacts are provided as-is for inference use.
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Model tree for Imbatmann/chatterbox-nepali-finetuned-quantized
Base model
ResembleAI/chatterbox