Update app.py

app.py

@@ -1,6 +1,28 @@
 import gradio as gr
 from PIL import Image
 
+
+from transformers import AutoConfig, AutoModelForCausalLM
+import torch
+
+# Determine if a GPU is available and set the device accordingly
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+
+# Load configuration from the base model
+config = AutoConfig.from_pretrained("microsoft/Florence-2-base-ft", trust_remote_code=True)
+
+# Load the model using the base model's configuration
+model = AutoModelForCausalLM.from_pretrained(
+    "fauzail/Florence-2-VQA",
+    config=config,
+    trust_remote_code=True
+).to(device)
+
+from transformers import AutoProcessor
+# Load the processor for the model
+processor = AutoProcessor.from_pretrained("fauzail/Florence-2-VQA", trust_remote_code=True)
+
 # Define the prediction function for Gradio
 def predict(image, question):
     inputs = processor(text=[question], images=[image], return_tensors="pt", padding=True).to(device)