HuggingFaceH4/mt_bench_prompts

Dataset

26

stars

8

commits

Jul 3, 2023

updated

evaluation

README

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 loading

To load this dataset, use 🤗 datasets:

from datasets import load_dataset
data = load_dataset(HuggingFaceH4/mt_bench_prompts, split="train")

Dataset creation

To create the dataset, we do the following for our internal tooling.

  • rename turns to prompts,
  • 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")

Contributors

natolambert

7 commits

NL

HuggingFaceH4/mt_bench_prompts

Dataset

26

stars

8

commits

Jul 3, 2023

updated

evaluation

README

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 loading

To load this dataset, use 🤗 datasets:

from datasets import load_dataset
data = load_dataset(HuggingFaceH4/mt_bench_prompts, split="train")

Dataset creation

To create the dataset, we do the following for our internal tooling.

  • rename turns to prompts,
  • 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")

Contributors

natolambert

7 commits

NL