Update app.py

app.py

@@ -2,7 +2,7 @@ import warnings
 import gradio as gr
 import torch
 from PIL import Image
-from transformers import AutoProcessor, Florence2ForConditionalGeneration
+from transformers import AutoProcessor, AutoModelForCausalLM
 from diffusers import AutoPipelineForImage2Image
 import random
 import numpy as np
@@ -31,7 +31,7 @@ pipe = AutoPipelineForImage2Image.from_pretrained(
 pipe.enable_vae_tiling()  # To help with memory for large images
 
 # Initialize Florence model with float32 to avoid dtype mismatch
-florence_model = Florence2ForConditionalGeneration.from_pretrained(
+florence_model = AutoModelForCausalLM.from_pretrained(
     'microsoft/Florence-2-large', 
     trust_remote_code=True,
     torch_dtype=torch.float32