Update app.py

app.py

@@ -1,24 +1,24 @@
-import streamlit as st
-from transformers import AutoModelForCausalLM, AutoTokenizer,pipeline
-import torch
-
-st.title("Text_Generator Fine tunning model")
-
-# Load model and tokenizer
-model_dir = "fine_tuned_model (1)"
-tokenizer = AutoTokenizer.from_pretrained(model_dir)
-model = AutoModelForCausalLM.from_pretrained(model_dir)
-
-
-code_generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
-
-prompt = "def quicksort(arr):"
-
-
-inputs_text=st.text_input("Please enter the text",value="I think I really like this place. Ayesha and I had a chance to visit  Cheuvront on a Monday night. It wasn\'t terribly busy when we arrived and we were warmly greeted. Unfortunately we were seated next to a loud group of young children that thought they knew something of the world ")
-
-if st.button("submit"):
-    generated_code = code_generator(inputs_text, max_length=200, num_return_sequences=1)
-    
-    st.write(generated_code[0]["generated_text"])
+import streamlit as st
+from transformers import AutoModelForCausalLM, AutoTokenizer,pipeline
+import torch
+
+st.title("Text_Generator Fine tunning model")
+
+# Load model and tokenizer
+model_dir = "fine_tuned_model (1)"
+tokenizer = AutoTokenizer.from_pretrained(model_dir)
+model = AutoModelForCausalLM.from_pretrained(model_dir)
+
+
+code_generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+prompt = "def quicksort(arr):"
+
+
+inputs_text=st.text_input("Please enter the text",value="def quicksort(arr):")
+
+if st.button("submit"):
+    generated_code = code_generator(inputs_text, max_length=200, num_return_sequences=1)
+    
+    st.write(generated_code[0]["generated_text"])