another

app.py

@@ -35,7 +35,7 @@ def predict(type, normalized_asm):
     input_ids = torch.LongTensor(tokenizer_output['input_ids'].tolist()).unsqueeze(0)
     nova_attention_mask = torch.LongTensor(tokenizer_output['nova_attention_mask']).unsqueeze(0)
 
-    outputs = model.generate(
+    output = model.generate(
         inputs=input_ids.cuda(), max_new_tokens=512, temperature=0.2, top_p=0.95,
         num_return_sequences=20, do_sample=True, nova_attention_mask=nova_attention_mask.cuda(),
         no_mask_idx=torch.LongTensor([tokenizer_output['no_mask_idx']]).cuda(), 
@@ -48,7 +48,7 @@ def predict(type, normalized_asm):
 
 demo = gr.Interface(
     fn=predict,
-    inputs=[gr.Text(label="Optimization Type", default="O0"), gr.Text(label="Normalized Assembly Code")],
+    inputs=[gr.Text(label="Optimization Type", value="O0"), gr.Text(label="Normalized Assembly Code")],
     outputs=gr.Text(label="Raw Nova Output"),
     description=frontmatter.load("README.md").content,
     #examples=examples