Fine-Tune ViT with Hugging Face Transformers using google/vit-base-patch16-224-in21k

AI Impact Summary

The article outlines an end-to-end workflow for fine-tuning a Vision Transformer (ViT) model using Hugging Face Transformers and Datasets. It demonstrates loading a pre-trained google/vit-base-patch16-224-in21k, constructing a ViTImageProcessor, converting images to pixel values, and applying real-time transforms with ds.with_transform for efficient batching. This matters to technical teams because it provides concrete APIs (ViTImageProcessor, google/vit-base-patch16-224-in21k, datasets, Trainer) and a ready-to-adapt recipe for domain-specific image classification projects such as plant health monitoring.