Update app.py

app.py

@@ -1,19 +1,13 @@
 import streamlit as st
-from transformers import AutoModelForCausalLM, AutoTokenizer
+from transformers import pipeline
 
-# Initialize model and tokenizer
-model_name = "RichardErkhov/mrm8488_-_gpt2-finetuned-recipes-cooking"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name)
+# Initialize the text generation pipeline with the GPT-2 fine-tuned recipe model
+pipe = pipeline("text-generation", model="mrm8488/gpt2-finetuned-recipes-cooking_v2")
 
 def generate_recipe(dish_name):
-    # Tokenize input
-    inputs = tokenizer(f"Recipe for {dish_name}:", return_tensors="pt")
-    outputs = model.generate(**inputs, max_length=300)
-    
-    # Decode generated text
-    recipe = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    return recipe
+    # Generate recipe using the text-generation pipeline
+    recipe = pipe(f"Recipe for {dish_name}:", max_length=300, num_return_sequences=1)
+    return recipe[0]['generated_text']
 
 # Streamlit app
 st.title("Cooking Recipe Generator")