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#TODO: set seed and argument for it
#TODO: use transformer library directly
import gradio as gr
from gradio import mix
from transformers import pipeline, set_seed
#title = "trustworthy artificial intelligence workshop - content generator"
description = "based on the gpt2 demo interface by <a href='https://huggingface.co/spaces/docs-demos/gpt2/tree/main'>ahsen khaliq</a>"
#io1 = gr.Interface.load("huggingface/distilgpt2")
generator = pipeline('text-generation', model='gpt2')
set_seed(42)
io2 = gr.Interface.load("huggingface/gpt2-large")
#io3 = gr.Interface.load("huggingface/gpt2-medium")
#io4 = gr.Interface.load("huggingface/gpt2-xl")
def inference(text):
"""
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)
"""
#outtext = io2(text)
outtext = generator(text, max_length=30, num_return_sequences=5)
return outtext
gr.Interface(
inference,
[gr.inputs.Textbox(label="Input", placeholder="trustworthy artificial intelligence")],
#,gr.inputs.Dropdown(choices=["distilgpt2","gpt2-medium","gpt2-large","gpt2-xl"], type="value", default="gpt2-medium", label="model")],
gr.outputs.Textbox(label="gpt-2 proposal"),
#title=title,
#description=description,
cache_examples=True).launch(enable_queue=True)
#TODO: add credits at bottom |