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
File size: 310 Bytes
6615096 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | # 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
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