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import gradio as gr
from happytransformer import HappyGeneration
happy_gen = HappyGeneration("GPT2", "DarwinAnim8or/GPT-Greentext-1.5b")
from happytransformer import GENSettings
def generate(text, length=100, penalty=3, temperature=0.8):
args_top_k = GENSettings(no_repeat_ngram_size=penalty, do_sample=True, top_k=80, temperature=temperature, max_length=length, early_stopping=False)
inputText = "Write a greentext from 4chan.org. The story should be like a bullet-point list using > as the start of each line. It must be funny and have a twist near the end.\n"
inputText += ">" + text + "\n>"
print(inputText)
result = happy_gen.generate_text(inputText, args=args_top_k)
generated_text = result.text #returns generated text only
#replace \n with actual newlines:
generated_text = generated_text.replace('\\n', '\n')
#clean up formatting:
generated_text = generated_text.replace('>', '\n>')
generated_text = generated_text.replace('\\"', "\"")
generated_text = ">" + text + "\n>" + generated_text #include our prompt in our response (partially)
return generated_text
examples = [
["be me"],
["be going to heaven"],
#["be going to work"],
#["be baking a pie"],
#["come home after another tiring day"],
["be a plague doctor"]
]
demo = gr.Interface(
fn=generate,
inputs=[
gr.inputs.Textbox(lines=5, label="Input Text"),
gr.inputs.Slider(5, 200, label='Length', default=100, step=5),
gr.inputs.Slider(1, 10, label='no repeat ngram size', default=2, step=1),
gr.inputs.Slider(0.0, 1.0, label='Temperature - control randomness', default=0.6, step=0.1)
],
outputs=gr.outputs.Textbox(label="Generated Text"),
examples=examples,
title="GPT-Greentext Playground",
description="Using the 1.5b size model. You may need to run it a few times in order to get something good!"
)
demo.launch() |