Image Classification
Transformers
Safetensors
English
vit
bio
eye_disease
diabetic_retionpathy
galucoma
cataract
Instructions to use msubhanahmed/VIT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use msubhanahmed/VIT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="msubhanahmed/VIT") 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("msubhanahmed/VIT") model = AutoModelForImageClassification.from_pretrained("msubhanahmed/VIT") - Notebooks
- Google Colab
- Kaggle
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Model tree for msubhanahmed/VIT
Base model
google/vit-base-patch16-224