Update ig.py

ig.py

@@ -1,14 +1,11 @@
 from transformers import AutoProcessor, AutoModelForCausalLM
 import gradio as gr
 import torch
-from transformers import AutoAdapterModel, AutoTokenizer
 
 model_name = "./" 
-model = AutoAdapterModel.from_pretrained(model_name)
-tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
 processor = AutoProcessor.from_pretrained("microsoft/git-base")
 
-
 def predict(image):
     try:
         # Prepare the image using the processor
@@ -45,4 +42,4 @@ with gr.Blocks() as demo:
 if __name__ == "__main__":
     demo.launch()  # Local machine only
     # demo.launch(server_name="0.0.0.0")  # LAN access to local machine
-    # demo.launch(share=True)  # Public access to local machine
+    # demo.launch(share=True)  # Public access to local machine