Compare results from the two fine-tuned models

app.py

@@ -5,64 +5,82 @@ import requests
 import gradio as gr
 from gradio import inputs, outputs
 
-ENDPOINT = (
-    "https://api-inference.huggingface.co/models/ceshine/t5-paraphrase-quora-paws"
+ENDPOINTS = (
+    "https://api-inference.huggingface.co/models/ceshine/t5-paraphrase-quora-paws",
+    "https://api-inference.huggingface.co/models/ceshine/t5-paraphrase-paws-msrp-opinosis",
 )
 
 
-def paraphrase(source_text: str, temperature: float):
-    if temperature > 0:
-        params = {
-            "do_sample": True,
-            "temperature": temperature,
-            "top_k": 5,
-            "num_return_sequences": 10,
-            "max_length": 100
-        }
-    else:
-        params = {
-            "num_beams": 10,
-            "num_return_sequences": 10,
-            "max_length": 100
-        }
-    res = requests.post(
-        ENDPOINT,
-        headers={"Authorization": f"Bearer {os.environ['TOKEN']}"},
-        data=json.dumps(
-            {
-                "inputs": "paraphrase: " + source_text,
-                "parameters": params,
+def get_fn(endpoint):
+    def paraphrase(source_text: str, temperature: float):
+        if temperature > 0:
+            params = {
+                "do_sample": True,
+                "temperature": temperature,
+                "top_k": 5,
+                "num_return_sequences": 10,
+                "max_length": 100,
             }
-        ),
-    )
-    if not (res.status_code == 200):
-        return f"Got a {res.status_code} status code from HuggingFace."
-    results = res.json()
-    # print(results)
-    outputs = [
-        x["generated_text"]
-        for x in results
-        if x["generated_text"].lower() != source_text.lower().strip()
-    ][:3]
-    text = ""
-    for i, output in enumerate(outputs):
-        text += f"{i+1}:  {output}\n\n"
-    return text
+        else:
+            params = {"num_beams": 10, "num_return_sequences": 10, "max_length": 100}
+        res = requests.post(
+            endpoint,
+            headers={"Authorization": f"Bearer {os.environ['TOKEN']}"},
+            data=json.dumps(
+                {
+                    "inputs": "paraphrase: " + source_text,
+                    "parameters": params,
+                }
+            ),
+        )
+        if not (res.status_code == 200):
+            return f"Got a {res.status_code} status code from HuggingFace."
+        results = res.json()
+        # print(results)
+        outputs = [
+            x["generated_text"]
+            for x in results
+            if x["generated_text"].lower() != source_text.lower().strip()
+        ][:3]
+        text = ""
+        for i, output in enumerate(outputs):
+            text += f"{i+1}:  {output}\n\n"
+        return text
+
+    return paraphrase
 
 
-interface = gr.Interface(
-    fn=paraphrase,
+interface_1 = gr.Interface(
+    fn=get_fn(ENDPOINTS[0]),
+    title="quora-paws",
     inputs=[
         inputs.Textbox(label="Source text"),
-        inputs.Number(default=0.0, label="Temperature (0 -> disable sampling and use beam search)"),
+        inputs.Number(
+            default=0.0, label="Temperature (0 -> disable sampling and use beam search)"
+        ),
     ],
-    outputs=outputs.Textbox(label="Generated text:"),
+    outputs=outputs.Textbox(label="quora-paws"),
+)
+
+interface_2 = gr.Interface(
+    fn=get_fn(ENDPOINTS[1]),
+    title="paws-msrp-opinosis",
+    inputs=[
+        inputs.Textbox(label="Source text"),
+        inputs.Number(
+            default=0.0, label="Temperature (0 -> disable sampling and use beam search)"
+        ),
+    ],
+    outputs=outputs.Textbox(label="paws-msrp-opinosis"),
+)
+
+gr.Parallel(
+    interface_1,
+    interface_2,
     title="T5 Sentence Paraphraser",
-    description="A paraphrasing model trained on PAWS and Quora datasets.",
+    description="Compare generated paraphrases from two models (`ceshine/t5-paraphrase-quora-paws` and `ceshine/t5-paraphrase-paws-msrp-opinosis`).",
     examples=[
         ["I bought a ticket from London to New York.", 0],
         ["Weh Seun spends 14 hours a week doing housework.", 1.2],
     ],
-)
-
-interface.launch(enable_queue=True)
+).launch(enable_queue=True)