Update app.py

app.py

@@ -1,25 +1,23 @@
 from transformers import AutoTokenizer, AutoModelForCausalLM
 from peft import PeftModel
-import accelerate
 import streamlit as st
 
 st.set_page_config(page_title = "Q&A Demo")
 st.header("Reviewer #2 Bot")
+title = st.text_input("Title : ")
+submit = st.button("Submit")
 
-model = AutoModelForCausalLM.from_pretrained("TinyLlama/TinyLlama-1.1B-Chat-v1.0").cuda()
+model = AutoModelForCausalLM.from_pretrained("TinyLlama/TinyLlama-1.1B-Chat-v1.0")
 model = PeftModel.from_pretrained(model, "shionhonda/tiny-llama-reviewer2-1.1B-dpo-lora")
 tokenizer = AutoTokenizer.from_pretrained("TinyLlama/TinyLlama-1.1B-Chat-v1.0")
 
-title = st.text_input("Title : ")
 prompt = tokenizer.apply_chat_template([
         {"role": "system", "content": "You are an experienced researcher and a reviewer of scientific papers. Given a title of the paper, write a review about it in one sentence."},
         {"role": "user", "content": title}
     ], tokenize=False, add_generation_prompt=True)
-inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
+inputs = tokenizer(prompt, return_tensors="pt")
 generate_ids = model.generate(inputs.input_ids, max_new_tokens=50, do_sample=True, temperature=0.5, top_k=50, top_p=0.95)
 
-submit = st.button("Submit")
-
 if submit:
     st.subheader("Reviewer #2:")
     st.write(tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0])