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Parent(s):
68b287a
init
Browse files- app.py +9 -52
- requirements.txt +1 -0
app.py
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# import gradio as gr
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# title = "SteelBERT"
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# examples = [
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# ['Paris is the [MASK] of France.', 'SteelBERT'],
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# ["A composite steel plate for marine construction was fabricated using 316L stainless steel.", 'SteelBERT'],
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# ["The use of composite [MASK] in construction is growing rapidly.", 'SteelBERT'],
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# ["Advances in [MASK] science are leading to stronger and more durable steel products.", 'SteelBERT'],
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# ["The corrosion resistance of stainless steel is attributed to the [MASK] of a passive film on the surface.", 'SteelBERT'],
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# ["Heat treatment of steel involves a controlled [MASK] and cooling process to alter its mechanical properties.", 'SteelBERT'],
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# ["Nano-engineered [MASK] have the potential to revolutionize the steel industry with their superior properties.", 'SteelBERT']
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# ]
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# # Load interfaces for different models
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# try:
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# io1 = gr.Interface.load("MGE-LLMs/SteelBERT")
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# import gradio as gr
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# title = "BERT"
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# description = "Gradio Demo for BERT. To use it, simply add your text, or click one of the examples to load them. Read more at the links below."
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# article = "<p style='text-align: center'><a href='https://arxiv.org/abs/1810.04805' target='_blank'>BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding</a></p>"
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# # examples = [
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# # ['Paris is the [MASK] of France.','bert-base-uncased']
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# # ]
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# examples = [
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# ['Paris is the [MASK] of France.', 'SteelBERT'],
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# ["A composite steel plate for marine construction was fabricated using 316L stainless steel.", 'SteelBERT'],
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# ["The use of composite [MASK] in construction is growing rapidly.", 'SteelBERT'],
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# ["Advances in [MASK] science are leading to stronger and more durable steel products.", 'SteelBERT'],
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# ["The corrosion resistance of stainless steel is attributed to the [MASK] of a passive film on the surface.", 'SteelBERT'],
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# ["Heat treatment of steel involves a controlled [MASK] and cooling process to alter its mechanical properties.", 'SteelBERT'],
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# ["Nano-engineered [MASK] have the potential to revolutionize the steel industry with their superior properties.", 'SteelBERT']
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# ]
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import gradio as gr
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title = "BERT"
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article = "<p style='text-align: center'><a href='https://arxiv.org/abs/1810.04805' target='_blank'>BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding</a></p>"
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examples = [
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['Paris is the [MASK] of France.',
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]
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io1 = gr.Interface.load("huggingface/bert-base-cased")
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io2 = gr.Interface.load("huggingface/bert-base-uncased")
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def inference(inputtext, model):
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if model == "bert-base-cased":
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outlabel = io1(inputtext)
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else:
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outlabel = io2(inputtext)
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return outlabel
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inputs = gr.Textbox(label="Context", lines=10)
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model_choice = gr.Dropdown(choices=["bert-base-cased", "bert-base-uncased"], label="Model", default="bert-base-cased")
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outputs = gr.Textbox(label="Output")
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gr.Interface(
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inputs=[
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outputs=
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examples=examples,
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article=article,
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title=title,
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description=description
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).launch(enable_queue=True)
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import gradio as gr
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title = "BERT"
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article = "<p style='text-align: center'><a href='https://arxiv.org/abs/1810.04805' target='_blank'>BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding</a></p>"
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examples = [
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['Paris is the [MASK] of France.','bert-base-cased']
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]
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io1 = gr.Interface.load("huggingface/bert-base-cased")
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io2 = gr.Interface.load("huggingface/bert-base-uncased")
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def inference(inputtext, model):
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if model == "bert-base-cased":
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outlabel = io1(inputtext)
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else:
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outlabel = io2(inputtext)
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return outlabel
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gr.Interface(
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inference,
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[gr.inputs.Textbox(label="Context",lines=10),gr.inputs.Dropdown(choices=["bert-base-cased","bert-base-uncased"], type="value", default="bert-base-cased", label="model")],
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[gr.outputs.Label(label="Output")],
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examples=examples,
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article=article,
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title=title,
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description=description).launch(enable_queue=True)
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requirements.txt
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gradio==3.43.1
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