Instructions to use hf-internal-testing/tiny-random-SwiftFormerForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SwiftFormerForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-SwiftFormerForImageClassification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-SwiftFormerForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-SwiftFormerForImageClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f204f1cab51a980cfa4b379d0a578bafeb39c3397f76d3d33e85eec4f820b0b5
- Size of remote file:
- 14 MB
- SHA256:
- abde0b776e7998ac2dd130dbbae52087571524e4aa27610b9e613d45404a5564
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