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!pip install transformers | |
import torch | |
from transformers import GPT2Tokenizer, GPT2LMHeadModel | |
# Load the GPT-3 model and tokenizer | |
tokenizer = GPT2Tokenizer.from_pretrained("stuheart86/EleutherAI-gpt-neo-1.3B") | |
model = GPT2LMHeadModel.from_pretrained("stuheart86/EleutherAI-gpt-neo-1.3B") | |
# Generate a story based on inputs | |
def generate_story(inputs): | |
genre = inputs["genre"] | |
story_teller = inputs["story_teller"] | |
story_telling_style = inputs["story_telling_style"] | |
creativity = inputs["creativity"] | |
# Use the inputs to prompt the GPT-3 model | |
prompt = f"Write a {genre} story told by a {story_teller} in a {story_telling_style} style with {creativity} creativity." | |
encoded_prompt = tokenizer.encode(prompt, return_tensors="pt") | |
generated_story = model.generate(encoded_prompt, max_length=200, num_return_sequences=1) | |
decoded_story = tokenizer.decode(generated_story.tolist()[0]) | |
return decoded_story | |