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
File size: 616 Bytes
4f93701 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | ---
license: apache-2.0
language:
- ml
base_model: ResembleAI/chatterbox
tags:
- text-to-speech
- tts
- malayalam
- chatterbox
- lora
---
# 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.json`
- `adapter_model.safetensors`
- `tokenizer_indic.json`
- `tokenizer_indic.json.manifest.json`
- `config_indic.py`
This is not a merged full model. Use it with the base Chatterbox non-turbo model and the included Indic tokenizer.
|