Instructions to use hf-tiny-model-private/tiny-random-UniSpeechForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-UniSpeechForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="hf-tiny-model-private/tiny-random-UniSpeechForSequenceClassification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-UniSpeechForSequenceClassification") model = AutoModelForAudioClassification.from_pretrained("hf-tiny-model-private/tiny-random-UniSpeechForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:c218fb93939625ded3bd48c03c67163e9adfce15e8873e913079d406f031d123
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size 135656
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