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import gradio as gr
from gradio import mix
title = "GPT2"
description = "Gradio Demo for OpenAI GPT2. To use it, simply add your text, or click one of the examples to load them. Read more at the links below."
article = "<p style='text-align: center'><a href='https://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_multitask_learners.pdf' target='_blank'>Language Models are Unsupervised Multitask Learners</a></p>"
examples = [
['Paris is the capital of',"gpt2-medium"]
]
io1 = gr.Interface.load("huggingface/distilgpt2")
io2 = gr.Interface.load("huggingface/gpt2-large")
io3 = gr.Interface.load("huggingface/gpt2-medium")
io4 = gr.Interface.load("huggingface/gpt2-xl")
def inference(text, model):
if model == "gpt2-large":
outtext = io2(text)
elif model == "gpt2-medium":
outtext = io3(text)
elif model == "gpt2-xl":
outtext = io4(text)
else:
outtext = io1(text)
return outtext
gr.Interface(
inference,
[gr.inputs.Textbox(label="Input"),gr.inputs.Dropdown(choices=["distilgpt2","gpt2-medium","gpt2-large","gpt2-xl"], type="value", default="gpt2-medium", label="model")
],
gr.outputs.Textbox(label="Output"),
examples=examples,
article=article,
title=title,
description=description).launch(enable_queue=True)
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