Instructions to use hf-internal-testing/tiny-random-SwiftFormerModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SwiftFormerModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-internal-testing/tiny-random-SwiftFormerModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-SwiftFormerModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-SwiftFormerModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0992662de315e50437ad97c3b242f370a1abe2758b4c9f68b68b79137fb2d1aa
- Size of remote file:
- 12.2 MB
- SHA256:
- cafea4be5efcf5a5b78bcae98b676c1da0afc67dc45a67f3d4cbe6d53b998238
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