Instructions to use facebook/regnet-y-040 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/regnet-y-040 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/regnet-y-040") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("facebook/regnet-y-040") model = AutoModelForImageClassification.from_pretrained("facebook/regnet-y-040", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from facebook/regnet-y-040: direct link, hf CLI and curl.
- Browser
- Download file 83 MB
-
https://huggingface.co/facebook/regnet-y-040/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://facebook/regnet-y-040/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/facebook/regnet-y-040/resolve/main/pytorch_model.bin
83 MB
- Xet hash:
- 457b947d5737f586d7e677c17a7e1af1df005e1e2f30ec4c12f6a6e79c83362d
- Size of remote file:
- 83 MB
- SHA256:
- c7cfc0e66a507c3283ac61962ff96b745f771d7429eac3e4fae5550c43dc25b0
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