Instructions to use mexca/mefarg-open-graph-au-resnet50-stage-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mexca/mefarg-open-graph-au-resnet50-stage-2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mexca/mefarg-open-graph-au-resnet50-stage-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from mexca/mefarg-open-graph-au-resnet50-stage-2: direct link, hf CLI and curl.
- Browser
- Download file 143 MB
-
https://huggingface.co/mexca/mefarg-open-graph-au-resnet50-stage-2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://mexca/mefarg-open-graph-au-resnet50-stage-2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mexca/mefarg-open-graph-au-resnet50-stage-2/resolve/main/pytorch_model.bin
143 MB
- Xet hash:
- dc9b34b5213d5c1eb07198ac694a43a2af83f279cf624c50033e04e3b7e6c64a
- Size of remote file:
- 143 MB
- SHA256:
- 2a5ba21719001c1cb68fe2052bee13aedead71114135ed3d3e5e6540f810798b
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