| import torch |
| from transformers import GPT2Tokenizer, GPT2LMHeadModel |
| import gradio as gr |
|
|
| |
| tokenizer = GPT2Tokenizer.from_pretrained("gpt2") |
| model = GPT2LMHeadModel.from_pretrained("gpt2") |
|
|
| def relay_story(input_text): |
| |
| input_ids = tokenizer.encode(input_text, return_tensors="pt") |
| output = model.generate(input_ids, max_length=100, num_return_sequences=1, pad_token_id=tokenizer.eos_token_id) |
| generated_text = tokenizer.decode(output[0], skip_special_tokens=True) |
| |
| return generated_text |
|
|
| |
| gr.Interface(fn=relay_story, inputs="text", outputs="text", title="Relay Story AI", description="๋น์ ์ ์ด์ผ๊ธฐ๋ฅผ ์์ํ์ธ์.").launch() |
|
|