Instructions to use hf-tiny-model-private/tiny-random-SEWForSequenceClassification 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-SEWForSequenceClassification 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-SEWForSequenceClassification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-SEWForSequenceClassification") model = AutoModelForAudioClassification.from_pretrained("hf-tiny-model-private/tiny-random-SEWForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 887cff031fcab12ae67748cce581e48709f20fa82d32a957333de8d7c611cf63
- Size of remote file:
- 240 kB
- SHA256:
- 96f05ad552b0d5ce7d40d83cc57b07b1688c3c9b0056af9a3ba167269bdfdc09
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