Spaces:
Paused
Paused
File size: 2,765 Bytes
7975f51 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 |
import json
import datasets
from typing import Any, Dict, List
_DESCRIPTION = "UltraChat: Large-scale, Informative, and Diverse Multi-round Dialogue Data."
_CITATION = """\
@misc{UltraChat,
author = {Ding, Ning and Chen, Yulin and Xu, Bokai and Hu, Shengding and Qin, Yujia and Liu, Zhiyuan and Sun, Maosong and Zhou, Bowen},
title = {UltraChat: A Large-scale Auto-generated Multi-round Dialogue Data},
year = {2023},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\\url{https://github.com/thunlp/ultrachat}},
}
"""
_HOMEPAGE = "https://huggingface.co/datasets/stingning/ultrachat"
_LICENSE = "cc-by-nc-4.0"
_BASE_DATA_URL = "https://huggingface.co/datasets/stingning/ultrachat/resolve/main/train_{idx}.jsonl"
class BelleMultiturn(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("0.0.0")
def _info(self) -> datasets.DatasetInfo:
features = datasets.Features({
"instruction": datasets.Value("string"),
"output": datasets.Value("string"),
"history": datasets.Sequence(datasets.Sequence(datasets.Value("string")))
})
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION
)
def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
file_paths = [dl_manager.download(_BASE_DATA_URL.format(idx=idx)) for idx in range(9)] # multiple shards
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"filepaths": file_paths
}
)
]
def _generate_examples(self, filepaths: List[str]) -> Dict[int, Dict[str, Any]]: # generate multi-turn chat for ChatGLM
for filepath in filepaths:
with open(filepath, "r", encoding="utf-8") as f:
for row in f:
try:
data = json.loads(row)
except:
continue
key = data["id"]
content = data["data"]
if len(content) % 2 == 1:
content.pop(-1)
if len(content) < 2:
continue
query = content[-2]
response = content[-1]
history = [[content[2*i], content[2*i+1]] for i in range(len(content) // 2 - 1)]
yield key, {
"instruction": query,
"output": response,
"history": history
}
|