Instructions to use hf-internal-testing/tiny-random-LevitForImageClassificationWithTeacher with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-LevitForImageClassificationWithTeacher with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-LevitForImageClassificationWithTeacher") 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-LevitForImageClassificationWithTeacher") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-LevitForImageClassificationWithTeacher") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa4d3857068c3e669a05c29c25af37681a03d0a5455471cf892132b7d07f616c
- Size of remote file:
- 28.2 MB
- SHA256:
- 9939d009b5e78d3841561e4132ed5d0d945707286619e3d1b1a0f37c51d5b815
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