Instructions to use michael-chan-000/tts-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use michael-chan-000/tts-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="michael-chan-000/tts-v2")# Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("michael-chan-000/tts-v2") model = AutoModelForTextToWaveform.from_pretrained("michael-chan-000/tts-v2") - Notebooks
- Google Colab
- Kaggle
| # Optional PromptTTS settings read by your miner.py. Example values. | |
| runtime: | |
| adapter: "example" | |
| device_preference: "cuda" | |
| dtype: "float32" | |
| generation: | |
| sample_rate: 24000 | |
| max_seconds: 20 | |
| guidance_scale: 1.0 | |
| io: | |
| output_format: "wav" | |
| limits: | |
| max_text_chars: 2000 | |
| max_instruction_chars: 600 | |