Instructions to use snap-research/efficientformer-l7-300 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use snap-research/efficientformer-l7-300 with timm:
import timm model = timm.create_model("hf-hub:snap-research/efficientformer-l7-300", pretrained=True) - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from snap-research/efficientformer-l7-300: direct link, hf CLI and curl.
- Browser
- Download file 330 MB
-
https://huggingface.co/snap-research/efficientformer-l7-300/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://snap-research/efficientformer-l7-300/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/snap-research/efficientformer-l7-300/resolve/main/pytorch_model.bin
330 MB
- Xet hash:
- 61247749b4685baa8cb428e47b889ddd88046a318b511ae594a16e80409dadf5
- Size of remote file:
- 330 MB
- SHA256:
- b7bb100f972867ca88e7e3ea1326185554ed756adcae6437b45f04044819ba91
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