Instructions to use hf-internal-testing/tiny-random-speech_to_text with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-speech_to_text with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-speech_to_text", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6c5f72251d861e4d284445113717cf6dca5118f8d325654196d21ca38595b76a
- Size of remote file:
- 1.46 MB
- SHA256:
- c17443480233215c494f693dfb0950d105d9b56559bef6e9544470ab89bbf230
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.