Instructions to use snap-research/efficientformer-l1-300 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use snap-research/efficientformer-l1-300 with timm:
import timm model = timm.create_model("hf-hub:snap-research/efficientformer-l1-300", pretrained=True) - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from snap-research/efficientformer-l1-300: direct link, hf CLI and curl.
- Browser
- Download file 49.4 MB
-
https://huggingface.co/snap-research/efficientformer-l1-300/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://snap-research/efficientformer-l1-300/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/snap-research/efficientformer-l1-300/resolve/main/pytorch_model.bin
49.4 MB
- Xet hash:
- 9a18ff139ffcd2719238b1b9d7515e8fa5d150f770e5d1a31823e40c8eeb075f
- Size of remote file:
- 49.4 MB
- SHA256:
- 62609fe0764f07c9a9aaf5d97da0ed6ee42630616dff958b88fddca5096bebc0
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