Update app.py

app.py

@@ -15,7 +15,7 @@ model = AutoModelForCausalLM.from_pretrained(
 )
 
 # Streamlit UI
-st.title("Eleanor Rigby - Lyrics Generation")
+st.title("Eleanor Rigby")
 
 # User input prompt
 user_prompt = st.text_area("Enter your prompt that can be song lyrics:", """Yesterday, I saw you in my dream""")
@@ -24,16 +24,12 @@ user_prompt = st.text_area("Enter your prompt that can be song lyrics:", """Yest
 if st.button("Generate Output"):
     instruct_prompt = "Instruct:You are a song writer and your main reference is The Beatles. Write a song lyrics by completing these words:"
     output_prompt = "Output:"
-    prompt = """ {0}{1}\n{2} """.format(instruct_prompt, user_prompt, output_prompt)
-    with torch.no_grad():
-        token_ids = tokenizer.encode(prompt, add_special_tokens=False, return_tensors="pt")
-        output_ids = model.generate(
-            token_ids.to(model.device),
-            max_new_tokens=512,
-            do_sample=True,
-            temperature=0.3
-        )
-
-    output = tokenizer.decode(output_ids[0][token_ids.size(1):])
+    input = inference_tokenizer(""" {0}{1}\n{2} """.format(instruct_prompt, user_prompt, output_prompt),
+                     return_tensors="pt",
+                     return_attention_mask=False,
+                     padding=True,
+                     truncation=True)
+    result = inference_model.generate(**input, repetition_penalty=1.2, max_length=1024)
+    output = inference_tokenizer.batch_decode(result, skip_special_tokens=True)[0]
     st.text("Generated Result:")
     st.write(output)