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add article and placeholder
Browse files
app.py
CHANGED
@@ -16,9 +16,7 @@ examples = [
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]
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title = "InstructionGen: Flan T5 Small & Bart Base"
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description = (
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"This demo compares the [flan-t5-small-instructiongen](https://huggingface.co/pszemraj/flan-t5-small-instructiongen) and [bart-base-instructiongen](https://huggingface.co/pszemraj/bart-base-instructiongen) models on 'creating' an instruction for arbitrary text."
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)
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article = "Both models generate instructions for Large Language Models (LLMs) from arbitrary text. They are trained on the [fleece2instructions](https://huggingface.co/datasets/pszemraj/fleece2instructions) dataset, which is a filtered/foramtted version of the [alpaca](https://huggingface.co/datasets/tatsu-lab/alpaca) dataset"
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@@ -34,13 +32,18 @@ def inference(text):
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io = gr.Interface(
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inference,
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gr.Textbox(
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outputs=[
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gr.Textbox(lines=3, label="Flan T5 Small", interactive=False),
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gr.Textbox(lines=3, label="Bart Base", interactive=False),
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],
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title=title,
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description=description,
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examples=examples,
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)
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io.launch()
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]
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title = "InstructionGen: Flan T5 Small & Bart Base"
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description = "This demo compares the [flan-t5-small-instructiongen](https://huggingface.co/pszemraj/flan-t5-small-instructiongen) and [bart-base-instructiongen](https://huggingface.co/pszemraj/bart-base-instructiongen) models on 'creating' an instruction for arbitrary text."
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article = "Both models generate instructions for Large Language Models (LLMs) from arbitrary text. They are trained on the [fleece2instructions](https://huggingface.co/datasets/pszemraj/fleece2instructions) dataset, which is a filtered/foramtted version of the [alpaca](https://huggingface.co/datasets/tatsu-lab/alpaca) dataset"
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io = gr.Interface(
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inference,
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gr.Textbox(
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lines=3,
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placeholder="Add text here & find out what intruction could cause an LLM to generate it!",
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),
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outputs=[
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gr.Textbox(lines=3, label="Flan T5 Small", interactive=False),
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gr.Textbox(lines=3, label="Bart Base", interactive=False),
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],
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title=title,
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description=description,
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article=article,
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examples=examples,
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cache_examples=False,
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)
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io.launch()
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