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import gradio as gr |
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demo = gr.Blocks() |
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name_list = ['huggingface/facebook/opt-13b', 'huggingface/bigscience/T0pp', 'huggingface/EleutherAI/gpt-j-6B', 'huggingface/gpt2-xl', 'huggingface/EleutherAI/gpt-neo-2.7B'] |
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examples = [ |
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["Q: A juggler can juggle 16 balls. Half of the balls are golf balls, and half of the golf balls are blue. How many blue golf balls are there?\nA: The answer (arabic numerals) is "], |
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["Q: A juggler can juggle 16 balls. Half of the balls are golf balls, and half of the golf balls are blue. How many blue golf balls are there?\nA: Let’s think step by step."], |
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["Q: Roger has 5 tennis balls. He buys 2 more cans of tennis balls. Each can has 3 tennis balls. How many tennis balls does he have now?\nA: The answer is 11.\nQ: A juggler can juggle 16 balls. Half of the balls are golf balls, and half of the golf balls are blue. How many blue golf balls are there?\nA:"], |
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["Q: Roger has 5 tennis balls. He buys 2 more cans of tennis balls. Each can has 3 tennis balls. How many tennis balls does he have now?\nA: Roger started with 5 balls. 2 cans of 3 tennis balls each is 6 tennis balls. 5 + 6 = 11. The answer is 11.\nQ:A juggler can juggle 16 balls. Half of the balls are golf balls, and half of the golf balls are blue. How many blue golf balls are there?\nA:"], |
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] |
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def calculator(num1, operation, num2): |
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if operation == "add": |
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return num1 + num2 |
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elif operation == "subtract": |
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return num1 - num2 |
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elif operation == "multiply": |
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return num1 * num2 |
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elif operation == "divide": |
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return num1 / num2 |
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def complete_with_gpt(text): |
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interfaces = [gr.Interface.load(name) for name in name_list] |
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return [interface(text) for interface in interfaces] |
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def set_example(example: list) -> dict: |
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return gr.Textbox.update(value=example[0]) |
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with gr.Blocks() as demo: |
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gr.Markdown( |
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""" |
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# Let’s think step by step Is all you need ? |
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""" |
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) |
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with gr.Box(): |
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with gr.Row(): |
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with gr.Column(): |
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input_text = gr.Textbox(label = "Write your riddle here", placeholder="Type here the riddles to see if LM can solve the questions", lines=4) |
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with gr.Row(): |
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btn = gr.Button("Laguage model think brrr ...") |
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example_text = gr.Dataset(components=[input_text], samples=examples) |
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example_text.click(fn=set_example, |
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inputs = example_text, |
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outputs= example_text.components) |
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with gr.Column(): |
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gr.Markdown("Let's see how different LM's multiply matrices/ think 💭") |
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btn.click(complete_with_gpt, inputs = input_text, outputs = [gr.Textbox(label=name_list[_], lines=4) for _ in range(len(name_list))]) |
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with gr.Column(): |
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gr.Markdown("In case you need to count to verify the answer, you can use the calculator below 😉 ") |
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num1 = gr.Number(placeholder="Type here the first number", lines=1) |
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num2 = gr.Number(placeholder="Type here the second number", lines=1) |
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operation = gr.Dropdown(["add", "subtract", "multiply", "divide"], placeholder="Type here the operation", lines=1) |
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with gr.Row(): |
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calculate = gr.Button("Calculate") |
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with gr.Column(): |
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calculate.click(calculator, inputs = [num1, operation, num2], outputs = gr.Textbox(label="Result", lines=1)) |
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gr.Markdown( |
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""" |
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<p style='text-align: center'><a href='https://arxiv.org/abs/2205.11916' target='_blank'>Large Language Models are Zero-Shot Reasoners</a> | <a href='https://github.com/kojima-takeshi188/zero_shot_cot target='_blank'>Github Repo</a></p> |
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""" |
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) |
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demo.launch() |
