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:
- ee26b6d3ca7dc6cc2830a644f4ea1b3809c42e2c42ae6d50b98eaa57b6a82c4a
- Size of remote file:
- 12.3 MB
- SHA256:
- 60a85942d67046254d3c80a1cefa47aff875e19c6020c116cdf4dc2947709f84
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