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a6255f8 d286a43 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | from transformers import GPT2LMHeadModel, GPT2Tokenizer
# Load pre-trained GPT-2 model and tokenizer
model_name = "gpt2" # You can use other GPT-2 variants like "gpt2-medium" or "gpt2-large"
model = GPT2LMHeadModel.from_pretrained(model_name)
tokenizer = GPT2Tokenizer.from_pretrained(model_name)
# Set the model to evaluation mode
model.eval()
def generate_recipe(prompt, max_length=150):
# Tokenize the input prompt
input_ids = tokenizer.encode(prompt, return_tensors="pt")
# Generate text based on the input prompt
output = model.generate(input_ids, max_length=max_length, num_beams=5, no_repeat_ngram_size=2, top_k=50, top_p=0.95, temperature=0.7)
# Decode the generated output
generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
return generated_text
# Take user input
user_input = input("Enter a cooking prompt to generate a recipe: ")
generated_recipe = generate_recipe(user_input)
print("Generated Recipe:")
print(generated_recipe)
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