Instructions to use hf-internal-testing/tiny-random-ViTHybridForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ViTHybridForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-ViTHybridForImageClassification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModelForImageClassification model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-ViTHybridForImageClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3fc51b436d1c9da90ef41b0e9726b62234d0bd0b1e3d0c1ce19c676ec0266ba4
- Size of remote file:
- 324 kB
- SHA256:
- 36532a7348f29a63c4fdbeb7866a49dc812f90847845d25dfe7b5fc002938fa0
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