Muennighoff commited on
Commit
ac3fdf5
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1 Parent(s): 842d3bc

Rename BTM

Browse files
Files changed (1) hide show
  1. app.py +14 -8
app.py CHANGED
@@ -54,7 +54,7 @@ TASK_LIST_CLASSIFICATION_NB = [
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  "NorwegianParliament",
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  "MassiveIntentClassification (nb)",
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  "MassiveScenarioClassification (nb)",
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- "ScalaNbClassification (nb)",
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  ]
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  TASK_LIST_CLASSIFICATION_SV = [
@@ -62,7 +62,6 @@ TASK_LIST_CLASSIFICATION_SV = [
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  "MassiveIntentClassification (sv)",
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  "MassiveScenarioClassification (sv)",
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  "NordicLangClassification",
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- "ScalaNbClassification",
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  "ScalaSvClassification",
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  "SweRecClassification",
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  ]
@@ -587,6 +586,15 @@ def get_dim_seq_size(model):
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  size = round(size["metadata"]["total_size"] / 1e9, 2)
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  return dim, seq, size
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  def add_rank(df):
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  cols_to_rank = [col for col in df.columns if col not in ["Model", "Model Size (GB)", "Embedding Dimensions", "Sequence Length"]]
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  if len(cols_to_rank) == 1:
@@ -659,8 +667,6 @@ def get_mteb_data(tasks=["Clustering"], langs=[], datasets=[], fillna=True, add_
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  df = pd.DataFrame(df_list)
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  # If there are any models that are the same, merge them
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  # E.g. if out["Model"] has the same value in two places, merge & take whichever one is not NaN else just take the first one
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- # Save to csv
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- df.to_csv("mteb.csv", index=False)
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  df = df.groupby("Model", as_index=False).first()
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  # Put 'Model' column first
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  cols = sorted(list(df.columns))
@@ -780,7 +786,7 @@ with block:
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  with gr.TabItem("English-X"):
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  with gr.Row():
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  gr.Markdown("""
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- **Bitext Mining Leaderboard ๐Ÿด๓ ง๓ ข๓ ณ๓ ฃ๓ ด๓ ฟ**
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  - **Metric:** [F1](https://huggingface.co/spaces/evaluate-metric/f1)
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  - **Languages:** 117 (Pairs of: English & other language)
@@ -801,13 +807,13 @@ with block:
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  inputs=[task_bitext_mining, lang_bitext_mining_other, datasets_bitext_mining_other],
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  outputs=data_bitext_mining,
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  )
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- with gr.TabItem("Other"):
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  with gr.Row():
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  gr.Markdown("""
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- **Bitext Mining Other Leaderboard ๐ŸŽŒ**
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  - **Metric:** [F1](https://huggingface.co/spaces/evaluate-metric/f1)
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- - **Languages:** 2 (Pair of: Danish & Bornholmsk)
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  - **Credits:** [Kenneth Enevoldsen](https://github.com/KennethEnevoldsen)
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  """)
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  with gr.Row():
 
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  "NorwegianParliament",
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  "MassiveIntentClassification (nb)",
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  "MassiveScenarioClassification (nb)",
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+ "ScalaNbClassification",
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  ]
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  TASK_LIST_CLASSIFICATION_SV = [
 
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  "MassiveIntentClassification (sv)",
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  "MassiveScenarioClassification (sv)",
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  "NordicLangClassification",
 
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  "ScalaSvClassification",
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  "SweRecClassification",
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  ]
 
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  size = round(size["metadata"]["total_size"] / 1e9, 2)
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  return dim, seq, size
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+ def make_datasets_clickable(df):
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+ """Does not work"""
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+ if "BornholmBitextMining" in df.columns:
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+ link = "https://huggingface.co/datasets/strombergnlp/bornholmsk_parallel"
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+ df = df.rename(
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+ columns={f'BornholmBitextMining': '<a target="_blank" style="text-decoration: underline" href="{link}">BornholmBitextMining</a>',})
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+ return df
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+
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+
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  def add_rank(df):
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  cols_to_rank = [col for col in df.columns if col not in ["Model", "Model Size (GB)", "Embedding Dimensions", "Sequence Length"]]
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  if len(cols_to_rank) == 1:
 
667
  df = pd.DataFrame(df_list)
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  # If there are any models that are the same, merge them
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  # E.g. if out["Model"] has the same value in two places, merge & take whichever one is not NaN else just take the first one
 
 
670
  df = df.groupby("Model", as_index=False).first()
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  # Put 'Model' column first
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  cols = sorted(list(df.columns))
 
786
  with gr.TabItem("English-X"):
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  with gr.Row():
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  gr.Markdown("""
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+ **Bitext Mining Leaderboard ๐ŸŽŒ**
790
 
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  - **Metric:** [F1](https://huggingface.co/spaces/evaluate-metric/f1)
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  - **Languages:** 117 (Pairs of: English & other language)
 
807
  inputs=[task_bitext_mining, lang_bitext_mining_other, datasets_bitext_mining_other],
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  outputs=data_bitext_mining,
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  )
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+ with gr.TabItem("Danish"):
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  with gr.Row():
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  gr.Markdown("""
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+ **Bitext Mining Danish Leaderboard ๐Ÿ‡ฉ๐Ÿ‡ฐ๐ŸŽŒ**
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  - **Metric:** [F1](https://huggingface.co/spaces/evaluate-metric/f1)
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+ - **Languages:** Danish & Bornholmsk (Danish Dialect)
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  - **Credits:** [Kenneth Enevoldsen](https://github.com/KennethEnevoldsen)
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  """)
819
  with gr.Row():