Instructions to use CarlosMM24/platzi-vit-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CarlosMM24/platzi-vit-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="CarlosMM24/platzi-vit-model") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("CarlosMM24/platzi-vit-model") model = AutoModelForImageClassification.from_pretrained("CarlosMM24/platzi-vit-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 02f9f750dc52cf3e1c345eebdd73192c8e451d6a15d7ed1f3202579a1cf744b0
- Size of remote file:
- 5.2 kB
- SHA256:
- ff0aeca256e4f4a6563275c9cb7a283194bdab896dcf5f85d51308702b11966e
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