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- README.md +1 -1
- app.py +0 -10
DESCRIPTION.md
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This text generation demo takes in input text and returns generated text. It uses the Transformers library to set up the model and has two examples.
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README.md
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---
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title: text_generation
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sdk: gradio
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---
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title: text_generation
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emoji: 🔥
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sdk: gradio
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app.py
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# URL: https://huggingface.co/spaces/gradio/text_generation
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# DESCRIPTION: This text generation demo takes in input text and returns generated text. It uses the Transformers library to set up the model and has two examples.
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# imports
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import gradio as gr
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from transformers import pipeline
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# loading the model
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generator = pipeline('text-generation', model='gpt2')
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# defining the core function
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def generate(text):
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result = generator(text, max_length=30, num_return_sequences=1)
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return result[0]["generated_text"]
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# defining examples
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examples = [
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["The Moon's orbit around Earth has"],
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["The smooth Borealis basin in the Northern Hemisphere covers 40%"],
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]
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# defining the interface
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demo = gr.Interface(
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fn=generate,
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inputs=gr.inputs.Textbox(lines=5, label="Input Text"),
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examples=examples
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)
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# launching
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demo.launch()
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import gradio as gr
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from transformers import pipeline
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generator = pipeline('text-generation', model='gpt2')
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def generate(text):
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result = generator(text, max_length=30, num_return_sequences=1)
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return result[0]["generated_text"]
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examples = [
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["The Moon's orbit around Earth has"],
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["The smooth Borealis basin in the Northern Hemisphere covers 40%"],
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]
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demo = gr.Interface(
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fn=generate,
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inputs=gr.inputs.Textbox(lines=5, label="Input Text"),
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examples=examples
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)
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demo.launch()
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