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:
- a309b02167bc880c6a82f853386fd84baa5d2f653ca7f968b1abeaf9803bd719
- Size of remote file:
- 12.3 MB
- SHA256:
- cdef4a8addaa3162855a82c6fe1288bcedc0e6f3f8846b3c673a76e2836c2daf
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