src/about.py

from dataclasses import dataclass
from enum import Enum


@dataclass
class Task:
    benchmark: str
    metric: str
    col_name: str
    category: str


# Select your tasks here
# ---------------------------------------------------
class Tasks(Enum):
    # task_key in the json file, metric_key in the json file, name to display in the leaderboard
    task0 = Task("anli_r1", "acc", "ANLI", "")
    task1 = Task("logiqa", "acc_norm", "LogiQA", "")


NUM_FEWSHOT = 0  # Change with your few shot
# ---------------------------------------------------


# Your leaderboard name
TITLE = """<h1 align="center" id="space-title">Demo leaderboard</h1>"""

# What does your leaderboard evaluate?
INTRODUCTION_TEXT = """
Intro text
"""

# Which evaluations are you running? how can people reproduce what you have?
LLM_BENCHMARKS_TEXT = f"""
## How it works

## Reproducibility
To reproduce our results, check out our repository [here](https://github.com/ttsds/ttsds).

"""

EVALUATION_QUEUE_TEXT = """
## How to submit a TTS model to the leaderboard

### 1) download the evaluation dataset
The evaluation dataset consists of wav / text pairs.
You can download it [here](https://huggingface.co/ttsds/eval).

### 2) create your TTS dataset
Create a dataset with your TTS model and the evaluation dataset.
Use the wav files as speaker reference and the text as the prompt.
Create a .tar.gz file with the dataset, and make sure to inlcude .wav files and .txt files.

### 3) submit your TTS dataset
Submit your dataset below.
"""

CITATION_BUTTON_LABEL = "Copy the following snippet to cite these results"
CITATION_BUTTON_TEXT = r"""
"""