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")# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-internal-testing/tiny-random-LevitForImageClassificationWithTeacher: direct link, hf CLI and curl.
- Browser
- Download file 28.3 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-LevitForImageClassificationWithTeacher/resolve/d8f0d0ebf329573ef82d39e1e50e87b30cdb3183/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-LevitForImageClassificationWithTeacher@d8f0d0ebf329573ef82d39e1e50e87b30cdb3183/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-LevitForImageClassificationWithTeacher/resolve/d8f0d0ebf329573ef82d39e1e50e87b30cdb3183/pytorch_model.bin
28.3 MB
- Xet hash:
- f630530fe608bc26e2205eada2696023c94c1548b7b7889393101c500020b169
- Size of remote file:
- 28.3 MB
- SHA256:
- da19bcb6ac5cc18436f4ea0370209fc531dabff6cc5b3954a2d5a2647fbd3a4a
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