Instructions to use rezajebeli97/vit_on_simple_data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rezajebeli97/vit_on_simple_data with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="rezajebeli97/vit_on_simple_data") 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("rezajebeli97/vit_on_simple_data") model = AutoModelForImageClassification.from_pretrained("rezajebeli97/vit_on_simple_data") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("rezajebeli97/vit_on_simple_data")
model = AutoModelForImageClassification.from_pretrained("rezajebeli97/vit_on_simple_data")Quick Links
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="rezajebeli97/vit_on_simple_data") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")