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from enum import Enum
from dataclasses import dataclass
# Define TaskInfo and Tasks as before
@dataclass
class TaskInfo:
benchmark: str
col_name: str
metric: str
# Replace these with actual subjects from your dataset
class Tasks(Enum):
History = TaskInfo(benchmark='History', col_name='History', metric='accuracy')
Mathematics = TaskInfo(benchmark='Mathematics', col_name='Mathematics', metric='accuracy')
Science = TaskInfo(benchmark='Science', col_name='Science', metric='accuracy')
Geography = TaskInfo(benchmark='Geography', col_name='Geography', metric='accuracy')
Literature = TaskInfo(benchmark='Literature', col_name='Literature', metric='accuracy')
Art = TaskInfo(benchmark='Art', col_name='Art', metric='accuracy')
Physics = TaskInfo(benchmark='Physics', col_name='Physics', metric='accuracy')
Chemistry = TaskInfo(benchmark='Chemistry', col_name='Chemistry', metric='accuracy')
Biology = TaskInfo(benchmark='Biology', col_name='Biology', metric='accuracy')
ComputerScience = TaskInfo(benchmark='Computer Science', col_name='Computer Science', metric='accuracy')
# Now include the variables expected by app.py
TITLE = """
<h1 align="center">🌐 LLM Leaderboard for MMMLU Evaluation 🌐</h1>
"""
INTRODUCTION_TEXT = """
Welcome to the LLM Leaderboard for the MMMLU dataset evaluation. This leaderboard displays the performance of various language models on the MMMLU dataset across different subjects.
"""
LLM_BENCHMARKS_TEXT = """
## About the MMMLU Benchmark
The Massive Multitask Multilingual Language Understanding (MMMLU) benchmark is designed to evaluate models on a wide range of subjects.
## How to Interpret the Leaderboard
- **Model**: The name of the model evaluated.
- **Average ⬆️**: The average accuracy across all subjects.
- **Subject Columns**: The accuracy (%) for each individual subject.
## How to Submit Your Model
Go to the **Submit here!** tab and provide your model details to have it evaluated and appear on the leaderboard.
"""
EVALUATION_QUEUE_TEXT = """
Below are the lists of models that have been evaluated, are currently being evaluated, or are pending evaluation.
"""
CITATION_BUTTON_LABEL = "Citation"
CITATION_BUTTON_TEXT = """
If you use this leaderboard or the MMMLU dataset in your research, please cite:
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