Instructions to use hf-tiny-model-private/tiny-random-SEWModel 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-SEWModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-SEWModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-SEWModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-SEWModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 45615808171cd00c6bd5b870e4382e102eabd64d253d7c94ad2a2e8dc0cf6d17
- Size of remote file:
- 204 kB
- SHA256:
- 0c1e11f1b01c93d6cd9eac6852cafb143c7e3863329a7bb32bf91f0c6fbe14b3
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