fix_model.py

from transformers import AutoImageProcessor
import os

print("--- Starting Fix Generation ---")
try:
    # 1. Fetch the correct manual (processor) from the base model
    print("Fetching processor from google/efficientnet-v2-s...")
    processor = AutoImageProcessor.from_pretrained("google/efficientnet-v2-s")

    # 2. Save it locally
    save_path = "./fix"
    if not os.path.exists(save_path):
        os.makedirs(save_path)
        
    processor.save_pretrained(save_path)
    print(f"\nSUCCESS! The file 'preprocessor_config.json' is now in the '{save_path}' folder.")
    print("\nNext Step: Upload this file to your Hugging Face repository.")
except Exception as e:
    print(f"\nERROR: {e}")