Instructions to use hf-internal-testing/tiny-random-EfficientFormerForImageClassificationWithTeacher with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-EfficientFormerForImageClassificationWithTeacher with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-EfficientFormerForImageClassificationWithTeacher") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForImageClassification model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-EfficientFormerForImageClassificationWithTeacher", device_map="auto") - Notebooks
- Google Colab
- Kaggle
hf-transformers-bot HF Staff
Update tiny models for EfficientFormerForImageClassificationWithTeacher
4589d85 Download pytorch_model.bin from hf-internal-testing/tiny-random-EfficientFormerForImageClassificationWithTeacher: direct link, hf CLI and curl.
- Browser
- Download file 1.84 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-EfficientFormerForImageClassificationWithTeacher/resolve/4589d859505fe94df3d85ee889a4eca539675574/pytorch_model.bin
- Command line
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hf download hf://hf-internal-testing/tiny-random-EfficientFormerForImageClassificationWithTeacher@4589d859505fe94df3d85ee889a4eca539675574/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-EfficientFormerForImageClassificationWithTeacher/resolve/4589d859505fe94df3d85ee889a4eca539675574/pytorch_model.bin
1.84 MB
- Xet hash:
- 921752ce2d579d1ef135fb8f8f5c49f2f2a1729c03e0a3357f40532a657fb69e
- Size of remote file:
- 1.84 MB
- SHA256:
- 8b03d8c1681d63e21ade9f6c835ff391e6a20b2fd32aa2e455bdd638cef78175
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