Instructions to use timm/regnety_160.deit_in1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/regnety_160.deit_in1k with timm:
import timm model = timm.create_model("hf-hub:timm/regnety_160.deit_in1k", pretrained=True) - Transformers
How to use timm/regnety_160.deit_in1k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="timm/regnety_160.deit_in1k") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/regnety_160.deit_in1k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from timm/regnety_160.deit_in1k: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/timm/regnety_160.deit_in1k/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://timm/regnety_160.deit_in1k/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/timm/regnety_160.deit_in1k/resolve/main/pytorch_model.bin
335 MB
- Xet hash:
- 5260d7c927895caa75fd5d5641888e3f815b7227cc63f8c5b4d4e89e57ad4750
- Size of remote file:
- 335 MB
- SHA256:
- e1c3c68fd13bc30f3e79fa299cd6e239186d7000b492a8bc27036f13d6f283cc
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