Update app.py

app.py

@@ -139,8 +139,8 @@ def m3(que, image):
     
 
 def m4(que, image):
-    processor3 = Pix2StructProcessor.from_pretrained('google/matcha-plotqa-v2')
-    model3 = Pix2StructForConditionalGeneration.from_pretrained('google/matcha-plotqa-v2')
+    processor3 = Pix2StructProcessor.from_pretrained('google/matcha-plotqa-v1')
+    model3 = Pix2StructForConditionalGeneration.from_pretrained('google/matcha-plotqa-v1')
 
     inputs = processor3(images=image, text=que, return_tensors="pt")
     predictions = model3.generate(**inputs, max_new_tokens=512)
@@ -158,11 +158,18 @@ def m5(que, image):
     return processor3.decode(predictions[0], skip_special_tokens=True)
 
 def m6(que, image):
-    model3 = Pix2StructForConditionalGeneration.from_pretrained("google/pix2struct-infographics-vqa-large")
-    processor3 = Pix2StructProcessor.from_pretrained("google/pix2struct-infographics-vqa-large")
+    # model3 = Pix2StructForConditionalGeneration.from_pretrained("google/pix2struct-infographics-vqa-large")
+    # processor3 = Pix2StructProcessor.from_pretrained("google/pix2struct-infographics-vqa-large")
     
+    # inputs = processor3(images=image, text=que, return_tensors="pt")
+    # predictions = model3.generate(**inputs)
+    # return processor3.decode(predictions[0], skip_special_tokens=True)
+
+    processor3 = Pix2StructProcessor.from_pretrained('google/matcha-plotqa-v1')
+    model3 = Pix2StructForConditionalGeneration.from_pretrained('google/matcha-plotqa-v1')
+
     inputs = processor3(images=image, text=que, return_tensors="pt")
-    predictions = model3.generate(**inputs)
+    predictions = model3.generate(**inputs, max_new_tokens=512)
     return processor3.decode(predictions[0], skip_special_tokens=True)