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/bc1aed649368c8c23fecdf2702283febbb74972c/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-UniSpeechSatForAudioFrameClassification@bc1aed649368c8c23fecdf2702283febbb74972c/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-UniSpeechSatForAudioFrameClassification/resolve/bc1aed649368c8c23fecdf2702283febbb74972c/pytorch_model.bin
134 kB
- Xet hash:
- 665b5f517d9237959eb3b2adf124e4f178da77ea24c1bd55a6111ad27cdbfc05
- Size of remote file:
- 134 kB
- SHA256:
- 2c46a8da09843560743ffa59e9d0b8b71fed4f3666010d110acb8f2356a563a1
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