Datasets:
Tasks:
Question Answering
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
< 1K
ArXiv:
Tags:
evaluation
License:
metadata
license: apache-2.0
task_categories:
- question-answering
- conversational
language:
- en
tags:
- evaluation
pretty_name: MT Bench
size_categories:
- n<1K
MT Bench by LMSYS
This set of evaluation prompts is created by the LMSYS org for better evaluation of chat models. For more information, see the paper.
Dataset creation
To create the dataset, we do the following for our internal tooling.
- rename
turns
toprompts
, - add empty
reference
to remaining prompts (for HF Datasets), - Use the following code to load and save as a dataset
from datasets import load_dataset
import hashlib
data = load_dataset("json", data_files="https://huggingface.co/datasets/HuggingFaceH4/mt_bench_prompts/raw/main/raw/question.jsonl", split="train")
# %% create_dataset.ipynb 11
def format_example(example):
return {
"prompt": example["prompt"],
"prompt_id": int(hashlib.sha256(''.join(example["prompt"]).encode("utf-8")).hexdigest(), 16) % (10 ** 8),
"category": example["category"],
"reference": example["reference"],
}
formatted_ds = data.map(format_example, num_proc=6, remove_columns=data.column_names)
#
formatted_ds.push_to_hub("HuggingFaceH4/mt_bench_prompts", split="train")