Instructions to use wgcv/platzi-vit-model-wgcv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wgcv/platzi-vit-model-wgcv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="wgcv/platzi-vit-model-wgcv") 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("wgcv/platzi-vit-model-wgcv") model = AutoModelForImageClassification.from_pretrained("wgcv/platzi-vit-model-wgcv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download bean_rust.jpeg from wgcv/platzi-vit-model-wgcv: direct link, hf CLI and curl.
- Browser
- Download file 64.4 kB
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https://huggingface.co/wgcv/platzi-vit-model-wgcv/resolve/main/bean_rust.jpeg
- Command line
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hf download hf://wgcv/platzi-vit-model-wgcv/bean_rust.jpeg
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curl -L -o bean_rust.jpeg https://huggingface.co/wgcv/platzi-vit-model-wgcv/resolve/main/bean_rust.jpeg
64.4 kB
