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/pangram.wav from itriedcoding/Sol: direct link, hf CLI and curl.
- Browser
- Download file 85.6 kB
-
https://huggingface.co/itriedcoding/Sol/resolve/main/examples/pangram.wav
- Command line
-
hf download hf://itriedcoding/Sol/examples/pangram.wav
-
curl -L -o pangram.wav https://huggingface.co/itriedcoding/Sol/resolve/main/examples/pangram.wav
85.6 kB
- Xet hash:
- c16fe1147ff060447ddd5953045eb69b3aafc9dd9bded8d21a0f94777577fa62
- Size of remote file:
- 85.6 kB
- SHA256:
- facf0b2f90f2cc4bf800c84a9dfcbfb71690a2741aa144be8a14e7a50ab6a877
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