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Create app.py
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app.py
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import gradio as gr
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from transformers import pipeline
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title = "tory Generator"
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# gpt-neo-2.7B gpt-j-6B
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def generate(text,the_model,max_length,temperature,repetition_penalty):
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generator = pipeline('text-generation', model=the_model)
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result = generator(text, num_return_sequences=3,
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max_length=max_length,
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temperature=temperature,
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repetition_penalty = repetition_penalty,
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no_repeat_ngram_size=2,early_stopping=False)
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return result[0]["generated_text"],result[1]["generated_text"],result[2]["generated_text"]
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def complete_with_gpt(text,context,the_model,max_length,temperature,repetition_penalty):
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# Use the last 50 characters of the text as context
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# text[:-context] +
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return generate(text[-context:],the_model,max_length,temperature,repetition_penalty)
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def send(text1,context,text2):
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return text1 + text2[context:]
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with gr.Blocks() as demo:
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textbox = gr.Textbox(placeholder="Type here and press enter...", lines=4)
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context = gr.Slider(value=50,label="Truncate input text length",minimum=1,maximum=300)
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the_model = gr.Dropdown(choices=['gpt2','gpt2-medium','gpt2-large','gpt2-xl'],value = 'gpt2',label="Choose model")
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max_length = gr.Slider(value=50,label="Max Generate Length",minimum=1,maximum=300)
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temperature = gr.Slider(value=1.0,label="Temperature",minimum=0.0,maximum=1.0,step=0.05)
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repetition_penalty = gr.Slider(value=1.1,label="Repetition penalty",minimum=0.2,maximum=2,step=0.1)
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output1 = gr.Textbox(lines=4)
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output2 = gr.Textbox(lines=4)
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output3 = gr.Textbox(lines=4)
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btn = gr.Button("Generate")
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btn.click(complete_with_gpt,inputs=[textbox,context,the_model,max_length,temperature,repetition_penalty], outputs=[output1,output2,output3])
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send1 = gr.Button("Send1 to Origin Textbox").click(send,inputs=[textbox,context,output1],outputs=textbox)
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send2 = gr.Button("Send2 to Origin Textbox").click(send,inputs=[textbox,context,output2],outputs=textbox)
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send3 = gr.Button("Send3 to Origin Textbox").click(send,inputs=[textbox,context,output3],outputs=textbox)
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demo.launch()
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