Instructions to use hf-internal-testing/tiny-random-SEWForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SEWForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="hf-internal-testing/tiny-random-SEWForSequenceClassification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-SEWForSequenceClassification") model = AutoModelForAudioClassification.from_pretrained("hf-internal-testing/tiny-random-SEWForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 577f2c98de6d62072e1c4769127d09de3829255f99c21857698f2226915ca93c
- Size of remote file:
- 258 kB
- SHA256:
- cb9cb474c02bfda6dee3e34a92f0228eb2edc4ed880aecbaa6d46c4b101a6158
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