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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"""
"""
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