Spaces:
Running
Running
Added emojis :D
Browse files
app.py
CHANGED
@@ -35,7 +35,7 @@ client_side = Category(
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category_id="client_side",
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title="Client Side Libraries π€",
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description="""
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## These are client side libraries to easily interact or run training with models, datasets and Spaces on Hugging Face Hub
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<br>
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""",
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news=[
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@@ -93,9 +93,9 @@ documentation = Category(
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)
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use_cases = Category(
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category_id="use_cases",
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title="Use Cases",
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description="""
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## These are resources compiled to demonstrate various use cases across different niches in software development.
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<br>
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""",
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news=[
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@@ -187,7 +187,7 @@ def category_tab(category):
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with gr.Blocks(css="#margin-top {margin-top: 15px} #center {text-align: center;} #news-tab {padding: 15px;} #news-tab h3 {margin: 0px; text-align: center;} #news-tab p {margin: 0px;} #article-button {flex-grow: initial;} #news-row {align-items: center;} #spaces-flex {flex-wrap: wrap; justify-content: space-around;} #space-card { display: flex; min-width: calc(90% / 3); max-width:calc(100% / 3); box-sizing: border-box;} #event-tabs {margin-top: 0px;} #spaces-flex > #paper-tile {min-width: 30%; max-width: 30%;}") as demo:
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with gr.Row(elem_id="center"):
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gr.Markdown("# Hugging Face for Software Developers")
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gr.Markdown("""
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At Hugging Face, we are committed to democratize cutting-edge of machine learning for everyone. This page is dedicated to highlighting tools, documentation and projects β inside and outside Hugging Face β tailored to get software developers build with machine learning.
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category_id="client_side",
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title="Client Side Libraries π€",
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description="""
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## These are client side libraries to easily interact or run training with models, datasets and Spaces on Hugging Face Hub π€
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<br>
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""",
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news=[
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)
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use_cases = Category(
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category_id="use_cases",
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title="Use Cases π",
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description="""
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## These are resources compiled to demonstrate various use cases across different niches in software development. π¨βπ»
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<br>
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""",
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news=[
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with gr.Blocks(css="#margin-top {margin-top: 15px} #center {text-align: center;} #news-tab {padding: 15px;} #news-tab h3 {margin: 0px; text-align: center;} #news-tab p {margin: 0px;} #article-button {flex-grow: initial;} #news-row {align-items: center;} #spaces-flex {flex-wrap: wrap; justify-content: space-around;} #space-card { display: flex; min-width: calc(90% / 3); max-width:calc(100% / 3); box-sizing: border-box;} #event-tabs {margin-top: 0px;} #spaces-flex > #paper-tile {min-width: 30%; max-width: 30%;}") as demo:
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with gr.Row(elem_id="center"):
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gr.Markdown("# Hugging Face for Software Developers π€ π π§βπ»")
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gr.Markdown("""
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At Hugging Face, we are committed to democratize cutting-edge of machine learning for everyone. This page is dedicated to highlighting tools, documentation and projects β inside and outside Hugging Face β tailored to get software developers build with machine learning.
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