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import gradio as gr | |
from transformers import GPT2LMHeadModel, AutoTokenizer, pipeline | |
import torch | |
device = 'cuda' if torch.cuda.is_available() else 'cpu' | |
# load pretrained + finetuned GPT2 | |
model = GPT2LMHeadModel.from_pretrained("./model/gpt2-355M") | |
model = model.to(device) | |
# create tokenizer | |
tokenizer = AutoTokenizer.from_pretrained( | |
"gpt2", | |
pad_token='<|endoftext|>' | |
) | |
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"].replace('"', '') # remove quotation marks | |
examples = [ | |
["Why does the lying news media"], | |
["The democrats have"], | |
["Today I'll be"], | |
] | |
demo = gr.Interface( | |
fn=generate, | |
inputs=gr.Textbox(lines=5, label="Prompt"), | |
outputs=gr.Textbox(label="Generated Trump Tweet"), | |
examples=examples | |
) | |
demo.launch() |