Instructions to use Praha-Labs/PrahaTTS-ML with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Chatterbox
How to use Praha-Labs/PrahaTTS-ML 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
PrahaTTS-ML
Malayalam LoRA adapter for ResembleAI Chatterbox non-turbo TTS.
This repository contains the selected 17k-step adapter checkpoint, chosen by listening quality rather than lowest training loss.
Contents
adapter_config.jsonadapter_model.safetensorstokenizer_indic.jsontokenizer_indic.json.manifest.jsonconfig_indic.py
This is not a merged full model. Use it with the base Chatterbox non-turbo model and the included Indic tokenizer.
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Model tree for Praha-Labs/PrahaTTS-ML
Base model
ResembleAI/chatterbox