Rename app_24_4_2024.py to app.py

app_24_4_2024.py → app.py

@@ -12,14 +12,14 @@ USE_LORA = False
 USE_QLORA = True
 
 processor = AutoProcessor.from_pretrained("HuggingFaceM4/idefics2-8b", do_image_splitting=False)
-# bnb_config = BitsAndBytesConfig(
-#         load_in_4bit=True,
-#         bnb_4bit_quant_type="nf4",
-#         bnb_4bit_compute_dtype=torch.float16
-#     ) 
+bnb_config = BitsAndBytesConfig(
+        load_in_4bit=True,
+        bnb_4bit_quant_type="nf4",
+        bnb_4bit_compute_dtype=torch.float16
+    ) 
 
 
-model = Idefics2ForConditionalGeneration.from_pretrained("HuggingFaceM4/idefics2-8b",load_in_4bit=True)
+model = Idefics2ForConditionalGeneration.from_pretrained("HuggingFaceM4/idefics2-8b",load_in_4bit=True,quantization_config=bnb_config)
 
 # if USE_QLORA or USE_LORA:
 #     lora_config = LoraConfig(
@@ -76,14 +76,14 @@ def model_inference(image, text):
 #     submit_btn = gr.Button("Generate")
 #     output = gr.Textbox(label="Model Output")
 
-with gr.Blocks(css=".input_image {max-width: 100%; border: 1px solid #ccc; box-shadow: 0 0 10px #ccc; margin-bottom: 10px;} .output_textbox {min-height: 100px;}") as demo:
-    gr.Markdown("## Enhanced IDEFICS2 Demo")
+with gr.Blocks(css="background-color:lightgrey;") as demo:
+    gr.Markdown("## IDEFICS2 Demo")
     with gr.Row():
         with gr.Column(scale=1):
             image_input = gr.Image(label="Upload Image", type="pil", tool="editor", height=480, width=640)
             query_input = gr.Textbox(label="Enter Prompt", placeholder="Type your prompt here...")
         with gr.Column(scale=1):
-            output = gr.Textbox(label="Model Output", interactive=True, placeholder="Output will be displayed here...")
+            output = gr.Textbox(label="Model Output", interactive=True, placeholder="Output will be displayed here...",lines=12)
 
     submit_btn = gr.Button("Generate")
     submit_btn.click(model_inference, inputs=[image_input, query_input], outputs=output)