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/en-gb.wav from itriedcoding/Sol: direct link, hf CLI and curl.
- Browser
- Download file 203 kB
-
https://huggingface.co/itriedcoding/Sol/resolve/main/examples/multilingual/en-gb.wav
- Command line
-
hf download hf://itriedcoding/Sol/examples/multilingual/en-gb.wav
-
curl -L -o en-gb.wav https://huggingface.co/itriedcoding/Sol/resolve/main/examples/multilingual/en-gb.wav
203 kB
- Xet hash:
- 8cdf75004bfcaed80c3d51775ac1a891840947f5bfee0d525fc53030da4269fd
- Size of remote file:
- 203 kB
- SHA256:
- 762e87a227411dc697ce011716a2181c379c1b4dafe0502d098c44fb18b61c33
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