Instructions to use hf-internal-testing/tiny-random-UniSpeechSatForAudioFrameClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-UniSpeechSatForAudioFrameClassification with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioFrameClassification processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-UniSpeechSatForAudioFrameClassification") model = AutoModelForAudioFrameClassification.from_pretrained("hf-internal-testing/tiny-random-UniSpeechSatForAudioFrameClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-internal-testing/tiny-random-UniSpeechSatForAudioFrameClassification: direct link, hf CLI and curl.
- Browser
- Download file 134 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-UniSpeechSatForAudioFrameClassification/resolve/f58d47591fdfabaa077635c60623653d86613af2/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-UniSpeechSatForAudioFrameClassification@f58d47591fdfabaa077635c60623653d86613af2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-UniSpeechSatForAudioFrameClassification/resolve/f58d47591fdfabaa077635c60623653d86613af2/pytorch_model.bin
134 kB
- Xet hash:
- 78e3d7feed3217afdc2e6a306c34a6cf9e6307cc5bd2042eeabd93e424269d66
- Size of remote file:
- 134 kB
- SHA256:
- d2365e9426f065100fe00b533770eca39552c492a264d842b65b358eb7893d70
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.