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•
f79ba24
1
Parent(s):
e7fb31c
move login to top of app
Browse files
app.py
CHANGED
@@ -182,6 +182,10 @@ with gr.Blocks() as demo:
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<center><i> 📁 From scattered files to a structured dataset in minutes 📁 </i></center>"""
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)
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gr.Markdown(description)
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gr.Markdown(
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"### 1. Upload Files\nClick 'Upload Files' to select text file(s). A preview will generate automatically"
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)
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@@ -221,10 +225,9 @@ with gr.Blocks() as demo:
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corpus_preview_df = gr.DataFrame(label="Dataset Preview")
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preview_summary = gr.Markdown()
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gr.Markdown("""### 4. Upload to the Hub
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-
After adjusting parameters and previewing the dataset, you can upload it to the Hugging Face Hub. Make sure
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""")
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with gr.Row():
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gr.LoginButton()
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with gr.Column():
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hub_id = gr.Textbox(value=None, label="Hub ID")
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private = gr.Checkbox(False, label="Upload dataset to a private repo?")
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<center><i> 📁 From scattered files to a structured dataset in minutes 📁 </i></center>"""
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)
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gr.Markdown(description)
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gr.Markdown(
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"### Sign in to Hugging Face Hub if you want to upload the dataset to the Hub"
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)
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gr.LoginButton()
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gr.Markdown(
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"### 1. Upload Files\nClick 'Upload Files' to select text file(s). A preview will generate automatically"
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)
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corpus_preview_df = gr.DataFrame(label="Dataset Preview")
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preview_summary = gr.Markdown()
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gr.Markdown("""### 4. Upload to the Hub
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After adjusting parameters and previewing the dataset, you can upload it to the Hugging Face Hub. Make sure you are signed in to your Hugging Face account. Specify the Hub ID and choose whether to make the dataset private. Click 'Upload to Hub' to complete the process.
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""")
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with gr.Row():
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with gr.Column():
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hub_id = gr.Textbox(value=None, label="Hub ID")
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private = gr.Checkbox(False, label="Upload dataset to a private repo?")
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