Upload app.py

app.py

@@ -68,7 +68,6 @@ def instruct_generate(
     """Generates a response based on a given instruction and an optional input.
     This script will only work with checkpoints from the instruction-tuned LLaMA-Adapter model.
     See `finetune_adapter.py`.
-
     Args:
         prompt: The prompt/instruction (Alpaca style).
         adapter_path: Path to the checkpoint with trained adapter weights, which are the output of
@@ -140,7 +139,7 @@ def create_instruct_demo():
                     lines=2, label="Instruction")
                 object_list = gr.Textbox(
                     lines=5, label="Input")
-                max_len = gr.Slider(minimum=1, maximum=512,
+                max_len = gr.Slider(minimum=1, maximum=1024,
                                     value=128, label="Max length")
                 with gr.Accordion(label='Advanced options', open=False):
                     temp = gr.Slider(minimum=0, maximum=1,
@@ -162,7 +161,7 @@ def create_instruct_demo():
             scene_name = os.path.basename(example_img_one).split(".")[0]
             example_object_list = example_dict[scene_name]["input_display"]
             example_instruction = example_dict[scene_name]["instruction"]
-            example_one = [example_img_one, example_instruction, example_object_list, 512, 0.8, 200]
+            example_one = [example_img_one, example_instruction, example_object_list, 1024, 0.8, 200]
             examples.append(example_one)
 
         gr.Examples(
@@ -188,5 +187,3 @@ with gr.Blocks(css='style.css') as demo:
         create_instruct_demo()
 
 demo.queue(api_open=True, concurrency_count=1).launch()
-
-