File size: 1,168 Bytes
3261604 d04d6b5 3261604 d04d6b5 3261604 d04d6b5 3261604 d04d6b5 | 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 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 | import torch
import gradio as gr
from transformers import GPT2LMHeadModel, GPT2Tokenizer
MODEL_NAME = "gpt2"
# Load model & tokenizer
tokenizer = GPT2Tokenizer.from_pretrained(MODEL_NAME)
model = GPT2LMHeadModel.from_pretrained(MODEL_NAME)
model.eval()
def generate_text(prompt, max_length):
inputs = tokenizer(prompt, return_tensors="pt")
with torch.no_grad():
outputs = model.generate(
**inputs,
max_length=max_length,
do_sample=True,
temperature=0.7,
top_p=0.95,
top_k=50
)
return tokenizer.decode(outputs[0], skip_special_tokens=True)
demo = gr.Interface(
fn=generate_text,
inputs=[
gr.Textbox(
label="Prompt",
placeholder="Enter your prompt..."
),
gr.Slider(
minimum=50,
maximum=250,
value=100,
step=10,
label="Max tokens"
),
],
outputs=gr.Textbox(label="Generated text"),
title="GPT-2 Text Generator",
description="GPT-2 deployed on Hugging Face Spaces using Gradio",
)
if __name__ == "__main__":
demo.launch()
|