Instructions to use gitgato/tr-xtts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gitgato/tr-xtts with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="gitgato/tr-xtts")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("gitgato/tr-xtts") model = AutoModelForTextToSpectrogram.from_pretrained("gitgato/tr-xtts", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download rng_state.pth from gitgato/tr-xtts: direct link, hf CLI and curl.
- Browser
- Download file 14.2 kB
-
https://huggingface.co/gitgato/tr-xtts/resolve/main/rng_state.pth
- Command line
-
hf download hf://gitgato/tr-xtts/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/gitgato/tr-xtts/resolve/main/rng_state.pth
14.2 kB
- Xet hash:
- c061c7c58fbb5b8575948687d57cc64edc72930544258396f35ac86222ac11ae
- Size of remote file:
- 14.2 kB
- SHA256:
- c31d5c2e1ede4f2e3fb805f57c4fc76f1c9db8c375b23e3049d8fecaf7190ac5
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