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
f86ea54 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/f86ea540d54508a2936f84de586ca352c76189d4/pytorch_model.bin
- Command line
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hf download hf://hf-internal-testing/tiny-random-EfficientFormerForImageClassificationWithTeacher@f86ea540d54508a2936f84de586ca352c76189d4/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-EfficientFormerForImageClassificationWithTeacher/resolve/f86ea540d54508a2936f84de586ca352c76189d4/pytorch_model.bin
1.84 MB
- Xet hash:
- 1bac4125dc177b43f513796eb8caeef441b39838695407d170f677b851e66f19
- Size of remote file:
- 1.84 MB
- SHA256:
- 9fcfda3052bae1d58b34a47f9ca0dc8ea965a1065ce64697443baa302391e95f
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