Instructions to use hf-internal-testing/tiny-random-PvtForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-PvtForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-PvtForImageClassification") 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-PvtForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-PvtForImageClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e1614b44ad407630081a692afe7c53e7cc468259137acdfd8d15b56c78912373
- Size of remote file:
- 3.38 MB
- SHA256:
- b230fb20161ffe11021d644f39b54b927cdd9977577a5070e26e63725e4f35bd
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