Instructions to use darklorddad/Model-Focalnet-Base-82 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use darklorddad/Model-Focalnet-Base-82 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="darklorddad/Model-Focalnet-Base-82") 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("darklorddad/Model-Focalnet-Base-82") model = AutoModelForImageClassification.from_pretrained("darklorddad/Model-Focalnet-Base-82", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from darklorddad/Model-Focalnet-Base-82: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/darklorddad/Model-Focalnet-Base-82/resolve/main/training_args.bin
- Command line
-
hf download hf://darklorddad/Model-Focalnet-Base-82/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/darklorddad/Model-Focalnet-Base-82/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 75112b07ed61379ca2d101bcd9fc45a56e6c94b03a3f5e385a360400f033e64a
- Size of remote file:
- 5.3 kB
- SHA256:
- 24779ba161a24fcf404cfce49654b0c18640007f7086a06316de954621441816
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