Instructions to use AhmedSayeem/VIT_Basic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AhmedSayeem/VIT_Basic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="AhmedSayeem/VIT_Basic") 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("AhmedSayeem/VIT_Basic") model = AutoModelForImageClassification.from_pretrained("AhmedSayeem/VIT_Basic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download images/ladders.jpg from AhmedSayeem/VIT_Basic: direct link, hf CLI and curl.
- Browser
- Download file 25.4 kB
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https://huggingface.co/AhmedSayeem/VIT_Basic/resolve/main/images/ladders.jpg
- Command line
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hf download hf://AhmedSayeem/VIT_Basic/images/ladders.jpg
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curl -L -o ladders.jpg https://huggingface.co/AhmedSayeem/VIT_Basic/resolve/main/images/ladders.jpg
25.4 kB
