Instructions to use hf-tiny-model-private/tiny-random-SEWDForSequenceClassification 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-SEWDForSequenceClassification 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-SEWDForSequenceClassification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-SEWDForSequenceClassification") model = AutoModelForAudioClassification.from_pretrained("hf-tiny-model-private/tiny-random-SEWDForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3993c93e1a28a31d612a0efc054ee7c812f9730428e39b8fd2cc17c28327142d
- Size of remote file:
- 324 kB
- SHA256:
- c91a04763f11bcae71ebdc5ab2fa992fdf14e83bbe1b3b30089de0b3924ffc60
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