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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5969289365590900c5b7dfdc63c201d54f6e526beacd2d31651db8c14d695fd7
- Size of remote file:
- 12.3 MB
- SHA256:
- 6b24deb908d8582984efd61317659b08dfdb567292d2ea38b67f6fc10c1375e0
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