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app.py

@@ -1,25 +1,11 @@
 import gradio as gr
-from transformers import AutoModelForCausalLM, AutoProcessor, AutoConfig
-import torch
+from transformers import AutoModelForCausalLM, AutoProcessor
 from PIL import Image
-
-# Custom configuration class
-class Florence2Config(AutoConfig):
-    def to_dict(self):
-        config_dict = super().to_dict()
-        return config_dict
+import torch
 
 # Load model and processor with trust_remote_code=True
-model = AutoModelForCausalLM.from_pretrained(
-    "mynkchaudhry/Florence-2-FT-DocVQA",
-    force_download=True,
-    trust_remote_code=True
-)
-processor = AutoProcessor.from_pretrained(
-    "mynkchaudhry/Florence-2-FT-DocVQA",
-    force_download=True,
-    trust_remote_code=True
-)
+model = AutoModelForCausalLM.from_pretrained("mynkchaudhry/Florence-2-FT-DocVQA", force_download=True, trust_remote_code=True)
+processor = AutoProcessor.from_pretrained("mynkchaudhry/Florence-2-FT-DocVQA", force_download=True, trust_remote_code=True)
 
 def generate_response(image, question):
     try: