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")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("AhmedSayeem/VIT_Basic") model = AutoModelForImageClassification.from_pretrained("AhmedSayeem/VIT_Basic") - Notebooks
- Google Colab
- Kaggle
VIT_Basic
Autogenerated by HuggingPics🤗🖼️
Create your own image classifier for anything by running the demo on Google Colab.
Report any issues with the demo at the github repo.
Example Images
chairs
hot dog
ice cream
ladders
tables
- Downloads last month
- 7
Evaluation results
- Accuracyself-reported0.911




