Instructions to use AFZAL0008/SwimV1Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AFZAL0008/SwimV1Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="AFZAL0008/SwimV1Base") 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("AFZAL0008/SwimV1Base") model = AutoModelForImageClassification.from_pretrained("AFZAL0008/SwimV1Base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from AFZAL0008/SwimV1Base: direct link, hf CLI and curl.
- Browser
- Download file 5.2 kB
-
https://huggingface.co/AFZAL0008/SwimV1Base/resolve/main/training_args.bin
- Command line
-
hf download hf://AFZAL0008/SwimV1Base/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/AFZAL0008/SwimV1Base/resolve/main/training_args.bin
5.2 kB
- Xet hash:
- e784d6f00f5f6bde62974627b73ab1cbc63292d282979bd499768ed232a01e91
- Size of remote file:
- 5.2 kB
- SHA256:
- 12d2816c1c18ca6b1ccaba238e0c8a809f24edea0436f6db3191c07b8dfb06d5
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