Update app.py

app.py

@@ -8,6 +8,7 @@ model = AutoModelForSequenceClassification.from_pretrained(
     trust_remote_code=True,
 )
 
+model.to('cuda')  # or 'cpu' if no GPU is available
 model.eval()
 
 def compute_scores(query, documents):
@@ -21,7 +22,8 @@ def compute_scores(query, documents):
     Returns:
         list of float: Scores representing the relevance of each document to the query.
     """
-    sentence_pairs = [[query, doc] for doc in documents]
+    documents_list = documents.split('\n')
+    sentence_pairs = [[query, doc] for doc in documents_list]
     scores = model.compute_score(sentence_pairs, max_length=1024)
     return scores.tolist()
 
@@ -29,8 +31,8 @@ def compute_scores(query, documents):
 iface = gr.Interface(
     fn=compute_scores,
     inputs=[
-        gr.inputs.Textbox(lines=2, placeholder="Enter your query here..."),
-        gr.inputs.Textbox(lines=8, placeholder="Enter your documents separated by newlines...")
+        gr.Textbox(lines=2, placeholder="Enter your query here..."),
+        gr.Textbox(lines=8, placeholder="Enter your documents separated by newlines...")
     ],
     outputs="json",
     title="Sentence Pair Scoring with Jina Reranker Model",