Instructions to use itriedcoding/Sol with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use itriedcoding/Sol with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="itriedcoding/Sol")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("itriedcoding/Sol") model = AutoModelForTextToSpectrogram.from_pretrained("itriedcoding/Sol", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download examples/multilingual/pt.wav from itriedcoding/Sol: direct link, hf CLI and curl.
- Browser
- Download file 190 kB
-
https://huggingface.co/itriedcoding/Sol/resolve/main/examples/multilingual/pt.wav
- Command line
-
hf download hf://itriedcoding/Sol/examples/multilingual/pt.wav
-
curl -L -o pt.wav https://huggingface.co/itriedcoding/Sol/resolve/main/examples/multilingual/pt.wav
190 kB
- Xet hash:
- 3738fee30ae283e27f282f7a80719faf2ec692aaedbda7e813ac916d99c26fd3
- Size of remote file:
- 190 kB
- SHA256:
- 2a44b4ed53d3af4852eaf3bcf726f90f86a7500b4b8a30a451fc68921fc6f8d2
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