Update app.py

app.py

@@ -84,7 +84,7 @@ def format_output(prediction):
     return prediction.replace('<0x0A>', '\n')
 
 # First model prediction ko-deplot
-@spaces.GPU(enable_queue=True,duration=120)
+@spaces.GPU(enable_queue=True,duration=100)
 def predict_model1(image):
     images = [image]
     inputs = processor1(images=images, text="What is the title of the chart", return_tensors="pt", padding=True)
@@ -116,25 +116,8 @@ def replace_unk(text):
     text = text.replace('<unk>', '')
     return text
 
-# Second model prediction aihub_deplot
-@spaces.GPU(enable_queue=True,duration=120)
-def predict_model2(image):
-    image = image.convert("RGB")
-    inputs = processor2(images=image, return_tensors="pt", max_patches=MAX_PATCHES).to(device)
 
-    flattened_patches = inputs.flattened_patches.to(device)
-    attention_mask = inputs.attention_mask.to(device)
-
-    model2.eval()
-   
-    with torch.no_grad():
-        deplot_generated_ids = model2.generate(flattened_patches=flattened_patches, attention_mask=attention_mask, max_length=1000)
-    generated_datatable = processor2.batch_decode(deplot_generated_ids, skip_special_tokens=False)[0]
-    generated_datatable = generated_datatable.replace("<pad>", "<unk>").replace("</s>", "<unk>")
-    refined_table = replace_unk(generated_datatable)
-    return refined_table
-
-@spaces.GPU(enable_queue=True,duration=120)
+@spaces.GPU(enable_queue=True,duration=100)
 def predict_model3(image):
     image=image.convert("RGB")
     input_prompt = "<extract_data_table> <s_answer>"