update

app.py

@@ -1,9 +1,18 @@
+import json
+import requests
 from relbert import RelBERT
 import gradio as gr
 
 model = RelBERT(model='relbert/relbert-roberta-large')
 
 
+def get_example():
+    url = "https://huggingface.co/datasets/relbert/analogy_questions/raw/main/dataset/sat/test.jsonl"
+    r = requests.get(url)
+    example = [json.loads(i) for i in r.content.decode().split('\n') if len(i) > 0]
+    return example
+
+
 def cosine_similarity(a, b, zero_vector_mask: float = -100):
     norm_a = sum(map(lambda x: x * x, a)) ** 0.5
     norm_b = sum(map(lambda x: x * x, b)) ** 0.5
@@ -68,6 +77,8 @@ def greet(
     return output
 
 
+examples = get_example()[:15]
+examples = [[','.join(i['stem'])] + [','.join(c) for c in i['choice'] + [''] * (10 - len(i['choice']))] for i in examples]
 demo = gr.Interface(
     fn=greet,
     inputs=[
@@ -84,10 +95,7 @@ demo = gr.Interface(
         gr.Textbox(lines=1, placeholder="Candidate Word Pair 10 (separate by comma)")
         ],
     outputs="label",
-    examples=[
-        ["beauty,aesthete", "pleasure,hedonist", "emotion,demagogue", "opinion,sympathizer", "seance,medium", "luxury,ascetic"] + [''] * 5,
-        ["classroom,desk", "bank,dollar", "church,pew", "studio,paintbrush", "museum,artifact"] + [''] * 6,
-    ],
+    examples=examples
 )
 demo.launch(show_error=True)