Formated code

app.py

@@ -4,12 +4,28 @@ from transformers import Qwen2VLForConditionalGeneration, Qwen2VLProcessor
 from qwen_vl_utils import process_vision_info
 import torch
 from PIL import Image
-import subprocess
 from datetime import datetime
 import numpy as np
 import os
 
 
+DESCRIPTION = """
+# Qwen2-VL-7B-trl-sft-ChartQA Demo
+
+This is a demo Space for a fine-tuned version of [Qwen2-VL-7B](https://huggingface.co/Qwen/Qwen2-VL-7B-Instruct) trained using [ChatQA dataset](https://huggingface.co/datasets/HuggingFaceM4/ChartQA).
+
+The corresponding model is located [here](https://huggingface.co/sergiopaniego/qwen2-7b-instruct-trl-sft-ChartQA).
+"""
+
+model_id = "Qwen/Qwen2-VL-7B-Instruct" 
+model = Qwen2VLForConditionalGeneration.from_pretrained(
+    model_id,
+    device_map="auto",
+    torch_dtype=torch.bfloat16,
+)
+adapter_path = "sergiopaniego/qwen2-7b-instruct-trl-sft-ChartQA"
+model.load_adapter(adapter_path)
+processor = Qwen2VLProcessor.from_pretrained(model_id)
 
 def array_to_image_path(image_array):
     if image_array is None:
@@ -30,41 +46,9 @@ def array_to_image_path(image_array):
     return full_path
 
 
-model_id = "Qwen/Qwen2-VL-7B-Instruct" 
-model = Qwen2VLForConditionalGeneration.from_pretrained(
-    model_id,
-    device_map="auto",
-    torch_dtype=torch.bfloat16,
-)
-adapter_path = "sergiopaniego/qwen2-7b-instruct-trl-sft-ChartQA"
-model.load_adapter(adapter_path)
-
-processor = Qwen2VLProcessor.from_pretrained(model_id)
-
-DESCRIPTION = """
-# Qwen2-VL-7B-trl-sft-ChartQA Demo
-
-This is a demo Space for a fine-tuned version of [Qwen2-VL-7B](https://huggingface.co/Qwen/Qwen2-VL-7B-Instruct) trained using [ChatQA dataset](https://huggingface.co/datasets/HuggingFaceM4/ChartQA).
-
-The corresponding model is located [here](https://huggingface.co/sergiopaniego/qwen2-7b-instruct-trl-sft-ChartQA)
-"""
-
-kwargs = {}
-kwargs['torch_dtype'] = torch.bfloat16
-
-user_prompt = '<|user|>\n'
-assistant_prompt = '<|assistant|>\n'
-prompt_suffix = "<|end|>\n"
-
 @spaces.GPU
 def run_example(image, text_input=None):
     image_path = array_to_image_path(image)
-    
-    print(image_path)
-    #model = models[model_id]
-    #processor = processors[model_id]
-
-    prompt = f"{user_prompt}<|image_1|>\n{text_input}{prompt_suffix}{assistant_prompt}"
     image = Image.fromarray(image).convert("RGB")
     messages = [
     {
@@ -121,13 +105,11 @@ with gr.Blocks(css=css) as demo:
         with gr.Row():
             with gr.Column():
                 input_img = gr.Image(label="Input Picture")
-                #model_selector = gr.Dropdown(choices=list(models.keys()), label="Model", value="sergiopaniego/qwen2-7b-instruct-trl-sft-ChartQA")
                 text_input = gr.Textbox(label="Question")
                 submit_btn = gr.Button(value="Submit")
             with gr.Column():
                 output_text = gr.Textbox(label="Output Text")
 
-        #submit_btn.click(run_example, [input_img, text_input, model_selector], [output_text])
         submit_btn.click(run_example, [input_img, text_input], [output_text])
 
 demo.queue(api_open=False)