Spaces:
Running
Running
Adding default values.
Browse files
app.py
CHANGED
@@ -180,55 +180,55 @@ def add_new_eval(
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with gr.Blocks() as demo:
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gr.Markdown("This is a super basic example 'frontend'. Fill out below then click **Run** to create the request file and launch the job.")
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gr.Markdown("The request file will be written so %s." % REQUESTS_DATASET_PATH)
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gr.Markdown("The job will be launched at [EnergyStarAI/launch-computation-example](https://huggingface.co/spaces/EnergyStarAI/launch-computation-example).")
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with gr.Row():
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gr.Markdown("# ✉️✨ Submit your model here!", elem_classes="markdown-text")
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demo.launch()
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with gr.Blocks() as demo:
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gr.Markdown("# This is a super basic example 'frontend'. Fill out below then click **Run** to create the request file and launch the job.")
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gr.Markdown("## The request file will be written so %s." % REQUESTS_DATASET_PATH)
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gr.Markdown("## The job will be launched at [EnergyStarAI/launch-computation-example](https://huggingface.co/spaces/EnergyStarAI/launch-computation-example).")
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with gr.Row():
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gr.Markdown("# ✉️✨ Submit your model here!", elem_classes="markdown-text")
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with gr.Row():
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with gr.Column():
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model_name_textbox = gr.Textbox(label="Model name", placeholder="lvwerra/distilbert-imdb")
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revision_name_textbox = gr.Textbox(label="Revision commit", placeholder="main")
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model_type = gr.Dropdown(
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choices=[t.to_str(" : ") for t in ModelType if t != ModelType.Unknown],
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label="Model type",
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placeholder="pretrained"
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multiselect=False,
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value=None,
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interactive=True,
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)
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with gr.Column():
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precision = gr.Dropdown(
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choices=[i.value.name for i in Precision if i != Precision.Unknown],
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label="Precision",
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multiselect=False,
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value="float16",
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interactive=True,
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)
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weight_type = gr.Dropdown(
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choices=[i.value.name for i in WeightType],
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label="Weights type",
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multiselect=False,
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value="Original",
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interactive=True,
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)
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with gr.Row():
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with gr.Column():
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submit_button = gr.Button("Run Analysis")
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submission_result = gr.Markdown()
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submit_button.click(
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fn=add_new_eval,
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inputs=[
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model_name_textbox,
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"",
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revision_name_textbox,
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precision,
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weight_type,
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model_type,
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],
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outputs=submission_result,
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)
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demo.launch()
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