98 lines
3.5 KiB
Python
98 lines
3.5 KiB
Python
import json
|
|
import datasets
|
|
from typing import Any, Dict, List
|
|
|
|
|
|
_DESCRIPTION = "Human preference data about helpfulness and harmlessness for ChatGLM."
|
|
_CITATION = ""
|
|
_HOMEPAGE = "https://huggingface.co/datasets/Anthropic/hh-rlhf"
|
|
_LICENSE = "mit"
|
|
_URL = "https://huggingface.co/datasets/Anthropic/hh-rlhf/resolve/main/"
|
|
_URLS = {
|
|
"train": [
|
|
_URL + "harmless-base/train.jsonl.gz",
|
|
_URL + "helpful-base/train.jsonl.gz",
|
|
_URL + "helpful-online/train.jsonl.gz",
|
|
_URL + "helpful-rejection-sampled/train.jsonl.gz"
|
|
],
|
|
"test": [
|
|
_URL + "harmless-base/test.jsonl.gz",
|
|
_URL + "helpful-base/test.jsonl.gz",
|
|
_URL + "helpful-online/test.jsonl.gz",
|
|
_URL + "helpful-rejection-sampled/test.jsonl.gz"
|
|
]
|
|
}
|
|
|
|
|
|
class HhRlhfEn(datasets.GeneratorBasedBuilder):
|
|
|
|
VERSION = datasets.Version("0.0.0")
|
|
|
|
def _info(self) -> datasets.DatasetInfo:
|
|
features = datasets.Features({
|
|
"instruction": datasets.Value("string"),
|
|
"output": datasets.Sequence(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_path = dl_manager.download_and_extract(_URLS)
|
|
return [
|
|
datasets.SplitGenerator(
|
|
name=datasets.Split.TRAIN,
|
|
gen_kwargs={
|
|
"filepaths": file_path["train"]
|
|
}
|
|
),
|
|
datasets.SplitGenerator(
|
|
name=datasets.Split.TEST,
|
|
gen_kwargs={
|
|
"filepaths": file_path["test"]
|
|
}
|
|
)
|
|
]
|
|
|
|
def _generate_examples(self, filepaths: List[str]) -> Dict[int, Dict[str, Any]]: # generate multi-turn chat for ChatGLM
|
|
key = 0
|
|
for filepath in filepaths:
|
|
with open(filepath, "r", encoding="utf-8") as f:
|
|
for row in f:
|
|
data = json.loads(row)
|
|
chosen = data["chosen"]
|
|
rejected = data["rejected"]
|
|
|
|
assist_idx = rejected.rfind("\n\nAssistant: ")
|
|
r_reject = rejected[assist_idx+13:].strip()
|
|
assist_idx = chosen.rfind("\n\nAssistant: ")
|
|
r_accept = chosen[assist_idx+13:].strip()
|
|
|
|
human_idx = chosen.rfind("\n\nHuman: ")
|
|
query = chosen[human_idx+9:assist_idx].strip()
|
|
prompt = chosen[:human_idx]
|
|
history = []
|
|
|
|
while prompt.rfind("\n\nAssistant: ") != -1:
|
|
assist_idx = prompt.rfind("\n\nAssistant: ")
|
|
human_idx = prompt.rfind("\n\nHuman: ")
|
|
if human_idx != -1:
|
|
old_query = prompt[human_idx+9:assist_idx].strip()
|
|
old_resp = prompt[assist_idx+13:].strip()
|
|
history.insert(0, (old_query, old_resp))
|
|
else:
|
|
break
|
|
prompt = prompt[:human_idx]
|
|
|
|
yield key, {
|
|
"instruction": query,
|
|
"output": [r_accept, r_reject],
|
|
"history": history
|
|
}
|
|
key += 1
|