Instructions to use awhiteside/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use awhiteside/model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="awhiteside/model")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("awhiteside/model") model = AutoModelForTextToWaveform.from_pretrained("awhiteside/model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from awhiteside/model: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/awhiteside/model/resolve/main/tokenizer.json
- Command line
-
hf download hf://awhiteside/model/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/awhiteside/model/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- 1f732a707b82c60c2febe62caf2cdfc24b6fa9ddd064c200b5b6eca738a94375
- Size of remote file:
- 17.2 MB
- SHA256:
- 529d18ee0f18a8a446ae0b4310c6675823231b366a7ea3fddfc488cf7f2277d6
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