Update app.py

app.py

@@ -1,13 +1,12 @@
 # Load model directly
 import streamlit as st
 
-from unsloth import FastLanguageModel
-model, tokenizer = FastLanguageModel.from_pretrained(
-        model_name = "shivam9980/mistral-7b-news", # YOUR MODEL YOU USED FOR TRAINING
-        max_seq_length = 2048,
-        dtype = None,
+from peft import AutoPeftModelForCausalLM
+from transformers import AutoTokenizer
+model = AutoPeftModelForCausalLM.from_pretrained(
+        "shivam9980/mistral-7b-news", # YOUR MODEL YOU USED FOR TRAINING
         load_in_4bit = True,)
-FastLanguageModel.for_inference(model) # Enable native 2x faster inference
+tokenizer = AutoTokenizer.from_pretrained("shivam9980/mistral-7b-news")
 
 # alpaca_prompt = You MUST copy from above!
 
@@ -33,4 +32,8 @@ inputs = tokenizer(
 
 outputs = model.generate(**inputs, max_new_tokens = 64, use_cache = True)
 results= tokenizer.batch_decode(outputs)
-st.write(results)
+out = results[0].split('\n')[-1]
+st.text_area(label='Headline',value=out[:len(out)-4])
+
+
+