a

app.py

@@ -14,17 +14,36 @@ model = AutoModelForCausalLM.from_pretrained(
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 
 
-title = "# Paper Review Generator"
-steps = """1. Converts uploaded pdf file to markdown. You can edit the intermediate markdown output.\n2. Generates a review for the paper"""
+title = "# Placeholder Title"
+steps = """Placeholder Description"""
+# steps = """1. Converts uploaded pdf file to markdown. You can edit the intermediate markdown output.\n2. Generates a review for the paper"""
 
 def process_file(file):
-
     return "Processed file"
 
 
-
+@spaces.GPU(duration=60)
 def generate(paper_text):
-    return "Success"
+    messages = [
+        {"role": "system", "content": "You are a pirate."},
+        {"role": "user", "content": paper_text}
+    ]
+    model_inputs = tokenizer.apply_chat_template(
+        messages,
+        add_generation_prompt=True
+    ).to(model.device)
+
+    generated_ids = model.generate(
+        **model_inputs,
+        max_new_tokens=256
+    )
+    generated_ids = [
+        output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
+    ]
+    
+    response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+    return response
+    # return "Success"