app.py

import gradio as gr
from transformers import GPT2LMHeadModel, pipeline
import torch

device = 'cuda' if torch.cuda.is_available() else 'cpu'

# load pretrained + finetuned GPT2
model = GPT2LMHeadModel.from_pretrained("./model", from_pt=True)
# model = GPT2LMHeadModel.from_pretrained("/zxc/model_epoch40_50w")
model = model.to(device)


# generator = pipeline('text-generation', model=model)

trump = pipeline("text-generation", model=model, tokenizer=tokenizer, config={"max_length":140})

def generate(text):
    result = trump(text, num_return_sequences=1)
    return result[0]["generated_text"]

examples = [
    ["Today I'll be"],
    ["Why does the lying news media"],
    ["The democrats have"]
]

demo = gr.Interface(
    fn=generate,
    inputs=gr.inputs.Textbox(lines=5, label="Input Text"),
    outputs=gr.outputs.Textbox(label="Generated Text"),
    examples=examples
)

demo.launch()