Omartificial-Intelligence-Space commited on
Commit
102204e
·
verified ·
1 Parent(s): 8f721a8

update app.py

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Files changed (1) hide show
  1. app.py +8 -5
app.py CHANGED
@@ -129,21 +129,21 @@ def evaluate_model(model_id):
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  # Define the Gradio interface
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  def display_results(model_name):
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- result_df, charts = evaluate_model(model_name)
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- return result_df, charts[0], charts[1], charts[2]
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  demo = gr.Interface(
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  fn=display_results,
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- inputs=gr.Textbox(label="Enter a Hugging Face Model ID", placeholder="e.g., sentence-transformers/all-MiniLM-L6-v2"),
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  outputs=[
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  gr.Dataframe(label="Evaluation Results"),
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  gr.Plot(label="Arabic Financial Dataset (Financial Evaluation)"),
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  gr.Plot(label="MLQA Arabic (Long Context Evaluation)"),
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  gr.Plot(label="ARCD (Short Context Evaluation)")
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  ],
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- title="Trireval for Arabic RAG Embedding Models",
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  description=(
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- "Evaluate your Sentence Transformer model's performance on **context and question retrieval** for Arabic datasets using RAG (Retrieval-Augmented Generation).\n"
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  "- **ARCD** evaluates short context retrieval performance.\n"
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  "- **MLQA Arabic** evaluates long context retrieval performance.\n"
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  "- **Arabic Financial Dataset** focuses on financial context retrieval.\n\n"
@@ -156,6 +156,9 @@ demo = gr.Interface(
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  css="footer {visibility: hidden;}"
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  )
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  demo.launch(share=True)
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  # Add the footer
 
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  # Define the Gradio interface
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  def display_results(model_name):
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+ result_df, chart1, chart2, chart3 = evaluate_model(model_name)
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+ return result_df, chart1, chart2, chart3
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  demo = gr.Interface(
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  fn=display_results,
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+ inputs=gr.Textbox(label="Enter Your Embedding Model ID", placeholder="e.g., Omartificial-Intelligence-Space/GATE-AraBert-v1"),
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  outputs=[
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  gr.Dataframe(label="Evaluation Results"),
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  gr.Plot(label="Arabic Financial Dataset (Financial Evaluation)"),
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  gr.Plot(label="MLQA Arabic (Long Context Evaluation)"),
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  gr.Plot(label="ARCD (Short Context Evaluation)")
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  ],
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+ title="Evaluation of Arabic Matryoshka Embedding Models on Retreival Tasks ",
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  description=(
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+ "Evaluate your Sentence Transformer model's performance on **context and question retrieval** for Arabic datasets for enhancing Arabic RAG.\n"
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  "- **ARCD** evaluates short context retrieval performance.\n"
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  "- **MLQA Arabic** evaluates long context retrieval performance.\n"
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  "- **Arabic Financial Dataset** focuses on financial context retrieval.\n\n"
 
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  css="footer {visibility: hidden;}"
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  )
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+ demo.launch(share=True)
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+
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+
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  demo.launch(share=True)
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  # Add the footer