first commit

app.py

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+import json
+
+import pandas as pd
+from datasets import load_dataset
+
+
+import gradio as gr
+from gradio_leaderboard import Leaderboard, SelectColumns, ColumnFilter
+import config
+from pathlib import Path
+import pandas as pd
+import random
+
+abs_path = Path(__file__).parent
+submissions = json.load(open(abs_path / "submissions.json"))
+
+TASKS = ["mmlu"]
+
+
+def load_submissions():
+    all_submissions = []
+
+    for submission in submissions["submissions"]:
+        ds = load_dataset(submission["results-dataset"], "results")
+        ds = ds.filter(lambda x: x["task"] in TASKS)
+
+        all_accuracy = []
+
+        for result in ds["train"]:
+            submission[result["task"]] = result["accuracy"]
+            all_accuracy.append(result["accuracy"])
+
+        submission["Average ⬆️"] = sum(all_accuracy) / len(all_accuracy)
+
+        submission["username"] = (
+            f"[{submission['username']}](https://huggingface.co/{submission['username']})"
+        )
+        submission["model_name"] = (
+            f"[{submission['model_name']}](https://huggingface.co/{submission['model_name']})"
+        )
+
+        submission["results-dataset"] = (
+            f"[🔗](https://huggingface.co/datasets/{submission['results-dataset']})"
+        )
+
+        all_submissions.append(submission)
+
+    all_submissions = pd.DataFrame(all_submissions)
+    return all_submissions
+
+
+with gr.Blocks() as demo:
+    gr.Markdown("""
+    # 🥇 a smol course leaderboad
+    
+    A leaderboard of smol course students' submissions. 
+    """)
+    with gr.Tabs():
+        with gr.Tab("Demo"):
+            Leaderboard(
+                value=load_submissions(),
+                select_columns=SelectColumns(
+                    default_selection=config.ON_LOAD_COLUMNS,
+                    cant_deselect=["username", "model_name"],
+                    label="Select Columns to Display:",
+                ),
+                search_columns=["username", "model_name"],
+                # hide_columns=["chapter"],
+                # filter_columns=[
+                #     "username",
+                #     "model_name",
+                #     # "Precision",
+                #     # ColumnFilter("MOE", type="boolean", default=False, label="MoE"),
+                #     # ColumnFilter("Flagged", type="boolean", default=False),
+                #     # ColumnFilter("#Params (B)", default=[30, 80]),
+                # ],
+                datatype=config.TYPES,
+                # column_widths=["2%", "33%"],
+            )
+        with gr.Tab("Docs"):
+            gr.Markdown((Path(__file__).parent / "docs.md").read_text())
+
+if __name__ == "__main__":
+    demo.launch()

config.py

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+import pandas as pd
+
+TYPES = [
+    "markdown",
+    "markdown",
+    "number",
+    "date",
+    "markdown",
+    "number",
+    "number",
+]
+
+ON_LOAD_COLUMNS = ["username", "model_name", "Average ⬆️", "mmlu"]
+
+# FILTER_COLUMNS = ["chapter"]
+
+
+NUMERIC_INTERVALS = {
+    "?": pd.Interval(-1, 0, closed="right"),
+    "~1.5": pd.Interval(0, 2, closed="right"),
+    "~3": pd.Interval(2, 4, closed="right"),
+    "~7": pd.Interval(4, 9, closed="right"),
+    "~13": pd.Interval(9, 20, closed="right"),
+    "~35": pd.Interval(20, 45, closed="right"),
+    "~60": pd.Interval(45, 70, closed="right"),
+    "70+": pd.Interval(70, 10000, closed="right"),
+}

docs.md

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+# Submission Instructions

submissions.json

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+{
+    "submissions": [
+        {
+            "username": "burtenshaw",
+            "model_name": "dave-the-demo",
+            "chapter": "1",
+            "submission_date": "2025-09-02",
+            "results-dataset": "burtenshaw/openbench-logs"
+        }
+    ]
+}