Instructions to use LeonelValencia/vit_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LeonelValencia/vit_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="LeonelValencia/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("LeonelValencia/vit_model") model = AutoModelForImageClassification.from_pretrained("LeonelValencia/vit_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0906700d31975ca8c4f7928cc96e58392e8d3c201018b846b922e349d85684bc
- Size of remote file:
- 4.98 kB
- SHA256:
- dbdf677ef995d50600a1ad87083c0ace0862b188eefcb606ffa21bf307d742a1
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