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/es.wav from itriedcoding/Sol: direct link, hf CLI and curl.
- Browser
- Download file 186 kB
-
https://huggingface.co/itriedcoding/Sol/resolve/main/examples/multilingual/es.wav
- Command line
-
hf download hf://itriedcoding/Sol/examples/multilingual/es.wav
-
curl -L -o es.wav https://huggingface.co/itriedcoding/Sol/resolve/main/examples/multilingual/es.wav
186 kB
- Xet hash:
- 5e365376f096a313e6ece98400ac53f850b7ebda259e3d8c7f470d325e16cbf7
- Size of remote file:
- 186 kB
- SHA256:
- 66443ab332569c728f7a3a1427c55b2b9db078ecb8c35e44f5d5582dd28dd690
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