Instructions to use hf-internal-testing/tiny-random-HieraForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-HieraForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-HieraForImageClassification") 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-HieraForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-HieraForImageClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5cf71be3ef1a42700cbc580a8cf3b315f4c5fd89b8e90d91d00fca5bef4fb1ba
- Size of remote file:
- 1.58 MB
- SHA256:
- f455bda6a1765fa4faa4a062e9244e8d9335e919d126c1a868843cdf051f1719
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