add max length

.ipynb_checkpoints/app-checkpoint.py

@@ -13,29 +13,26 @@ def query(payload):
 
 def infer(s1, s2):
     model_input = "Classify and explain the relationship between this pair of sentences: <S1> "+s1+" </S1><S2> "+s2+" </S2>"
-    data = query(model_input)
+    data = query({
+        "inputs": model_input,
+        "parameters": {"max_length": 128},
+    })
 
     if "error" in data:
         return "Error: "+ data["error"]
     elif "generated_text" in data[0]:
-        return data[0]["generated_text"]
+        output = data[0]["generated_text"].replace(" ; ", "\n")
+        return output
     else:
         return data
 
 title = "Paraphrase Classification and Explanation"
 desc = "Classify and explain the semantic relationship between the two sentences"
-long_desc = "This is a Flan-T5-Large model fine-tuned to perform paraphrase classification and explanation. It takes in two sentences as inputs."
+long_desc = "This is a Flan-T5-Large model fine-tuned to perform paraphrase classification and explanation. It takes in two sentences as inputs. Feel free to modify the example inputs or enter in your own sentences."
 
 s1 = gr.Textbox(value="On Monday, Tom went to the market.",label="Sentence 1")
 s2 = gr.Textbox(value="Tom went to the market.",label="Sentence 2")
 
-examples = gr.Examples(
-        examples=[
-            ["one", "two"],
-        ],
-        inputs=[s1, s2],
-)
-
 demo = gr.Interface(fn=infer, inputs=[s1,s2], outputs="text",
                     title=title,
                     description=desc,

app.py

@@ -13,29 +13,26 @@ def query(payload):
 
 def infer(s1, s2):
     model_input = "Classify and explain the relationship between this pair of sentences: <S1> "+s1+" </S1><S2> "+s2+" </S2>"
-    data = query(model_input)
+    data = query({
+        "inputs": model_input,
+        "parameters": {"max_length": 128},
+    })
 
     if "error" in data:
         return "Error: "+ data["error"]
     elif "generated_text" in data[0]:
-        return data[0]["generated_text"]
+        output = data[0]["generated_text"].replace(" ; ", "\n")
+        return output
     else:
         return data
 
 title = "Paraphrase Classification and Explanation"
 desc = "Classify and explain the semantic relationship between the two sentences"
-long_desc = "This is a Flan-T5-Large model fine-tuned to perform paraphrase classification and explanation. It takes in two sentences as inputs."
+long_desc = "This is a Flan-T5-Large model fine-tuned to perform paraphrase classification and explanation. It takes in two sentences as inputs. Feel free to modify the example inputs or enter in your own sentences."
 
 s1 = gr.Textbox(value="On Monday, Tom went to the market.",label="Sentence 1")
 s2 = gr.Textbox(value="Tom went to the market.",label="Sentence 2")
 
-examples = gr.Examples(
-        examples=[
-            ["one", "two"],
-        ],
-        inputs=[s1, s2],
-)
-
 demo = gr.Interface(fn=infer, inputs=[s1,s2], outputs="text",
                     title=title,
                     description=desc,