Instructions to use AFZAL0008/SwimV3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AFZAL0008/SwimV3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="AFZAL0008/SwimV3") 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/SwimV3") model = AutoModelForImageClassification.from_pretrained("AFZAL0008/SwimV3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from AFZAL0008/SwimV3: direct link, hf CLI and curl.
- Browser
- Download file 5.2 kB
-
https://huggingface.co/AFZAL0008/SwimV3/resolve/main/training_args.bin
- Command line
-
hf download hf://AFZAL0008/SwimV3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/AFZAL0008/SwimV3/resolve/main/training_args.bin
5.2 kB
- Xet hash:
- f8c2ac7c4a0a154395336a6a25cecd63b29e60a1a5e0d2552e40e7d1f48e7ded
- Size of remote file:
- 5.2 kB
- SHA256:
- 01bf27bccbe3e37c53cc5b599c5251d83e2d4b158290887684135811171989d3
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