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import gradio as gr
import torch
from transformers import GPT2LMHeadModel, GPT2Tokenizer
# Load model and tokenizer from Hugging Face
def load_model():
model_name = "aayushraina/gpt2shakespeare"
tokenizer = GPT2Tokenizer.from_pretrained(model_name)
model = GPT2LMHeadModel.from_pretrained(model_name)
model.eval()
return model, tokenizer
# Text generation function
def generate_text(prompt, max_length=500, temperature=0.8, top_k=40, top_p=0.9):
# Encode the input prompt
input_ids = tokenizer.encode(prompt, return_tensors='pt')
# Generate text
with torch.no_grad():
output = model.generate(
input_ids,
max_length=max_length,
temperature=temperature,
top_k=top_k,
top_p=top_p,
do_sample=True,
pad_token_id=tokenizer.eos_token_id,
num_return_sequences=1
)
# Decode and return the generated text
generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
return generated_text
# Load model and tokenizer globally
print("Loading model and tokenizer...")
model, tokenizer = load_model()
print("Model loaded successfully!")
# Create Gradio interface
demo = gr.Interface(
fn=generate_text,
inputs=[
gr.Textbox(label="Enter your prompt", placeholder="Start your text here...", lines=2),
gr.Slider(minimum=10, maximum=1000, value=500, step=10, label="Maximum Length"),
gr.Slider(minimum=0.1, maximum=2.0, value=0.8, step=0.1, label="Temperature"),
gr.Slider(minimum=1, maximum=100, value=40, step=1, label="Top-k"),
gr.Slider(minimum=0.1, maximum=1.0, value=0.9, step=0.1, label="Top-p"),
],
outputs=gr.Textbox(label="Generated Text", lines=10),
title="Shakespeare-style Text Generator",
description="""Generate Shakespeare-style text using a fine-tuned GPT-2 model.
Parameters:
- Temperature: Higher values make the output more random, lower values more focused
- Top-k: Number of highest probability vocabulary tokens to keep for top-k filtering
- Top-p: Cumulative probability for nucleus sampling
""",
examples=[
["First Citizen:", 500, 0.8, 40, 0.9],
["To be, or not to be,", 500, 0.8, 40, 0.9],
["Friends, Romans, countrymen,", 500, 0.8, 40, 0.9],
["O Romeo, Romeo,", 500, 0.8, 40, 0.9],
["Now is the winter of our discontent", 500, 0.8, 40, 0.9]
]
)
# Launch the app
if __name__ == "__main__":
demo.launch() |