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from dataclasses import dataclass
from enum import Enum
@dataclass
class Task:
benchmark: str
metric: str
col_name: str
# Init: to update with your specific keys
class Tasks(Enum):
# task_key in the json file, metric_key in the json file, name to display in the leaderboard
task0 = Task("task_name1", "metric_name", "First task")
task1 = Task("task_name2", "metric_name", "Second task")
# Your leaderboard name
TITLE = """<h1 align="center" id="space-title">🏆 Auto Arena of LLMs</h1>"""
# subtitle
SUB_TITLE = """<h2 align="center" id="space-title">Automating LLM Evaluations with Agent Peer-battles and Committee Discussions</h1>"""
# What does your leaderboard evaluate?
INTRODUCTION_TEXT = """
This leaderboard is from a completely automated large language model (LLM) evaluation framework by employing various LLM agents in peer-battles and committee discussions.
You can find more details from the [project page](https://auto-arena.github.io/) and our [paper]().
"""
# For additional details such as datasets, evaluation criteria, and reproducibility, please refer to the "📝 About" tab.
# Stay tuned for the *SeaBench leaderboard* - focusing on evaluating the model's ability to respond to general human instructions in real-world multi-turn settings.
# """
# Which evaluations are you running? how can people reproduce what you have?
LLM_BENCHMARKS_TEXT = f"""
```
"""
# You can find the detailed numerical results in the results Hugging Face dataset: https://huggingface.co/datasets/SeaLLMs/SeaExam-results
EVALUATION_QUEUE_TEXT = """
"""
CITATION_BUTTON_LABEL = ""
CITATION_BUTTON_TEXT = r"""
"""
CONTACT_TEXT = f"""
## Contact
"""
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