forked from p04798526/LLaMA-Factory-Mirror
Follow HF_ENDPOINT environment variable
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@ -1,6 +1,8 @@
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import os
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import json
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import datasets
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_HF_ENDPOINT = os.getenv("HF_ENDPOINT", "https://huggingface.co")
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_DESCRIPTION = "BELLE multiturn chat dataset."
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@ -13,9 +15,9 @@ _CITATION = """\
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}
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"""
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_HOMEPAGE = "https://huggingface.co/datasets/BelleGroup/multiturn_chat_0.8M"
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_HOMEPAGE = f"{_HF_ENDPOINT}/datasets/BelleGroup/multiturn_chat_0.8M"
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_LICENSE = "gpl-3.0"
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_URL = "https://huggingface.co/datasets/BelleGroup/multiturn_chat_0.8M/resolve/main/multiturn_chat_0.8M.json"
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_URL = f"{_HF_ENDPOINT}/datasets/BelleGroup/multiturn_chat_0.8M/resolve/main/multiturn_chat_0.8M.json"
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class BelleMultiturn(datasets.GeneratorBasedBuilder):
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@ -1,13 +1,17 @@
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import os
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import json
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import datasets
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from typing import List
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_HF_ENDPOINT = os.getenv("_HF_ENDPOINT", "https://huggingface.co")
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_DESCRIPTION = "Human preference data about helpfulness and harmlessness."
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_CITATION = ""
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_HOMEPAGE = "https://huggingface.co/datasets/Anthropic/hh-rlhf"
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_HOMEPAGE = f"{_HF_ENDPOINT}/datasets/Anthropic/hh-rlhf"
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_LICENSE = "mit"
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_URL = "https://huggingface.co/datasets/Anthropic/hh-rlhf/resolve/main/"
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_URL = f"{_HF_ENDPOINT}/datasets/Anthropic/hh-rlhf/resolve/main/"
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_URLS = {
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"train": [
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_URL + "harmless-base/train.jsonl.gz",
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@ -1,7 +1,9 @@
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import os
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import json
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import datasets
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from typing import List
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_HF_ENDPOINT = os.getenv("_HF_ENDPOINT", "https://huggingface.co")
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_DESCRIPTION = "UltraChat: Large-scale, Informative, and Diverse Multi-round Dialogue Data."
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@ -16,9 +18,9 @@ _CITATION = """\
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}
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"""
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_HOMEPAGE = "https://huggingface.co/datasets/stingning/ultrachat"
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_HOMEPAGE = f"{_HF_ENDPOINT}/datasets/stingning/ultrachat"
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_LICENSE = "cc-by-nc-4.0"
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_BASE_DATA_URL = "https://huggingface.co/datasets/stingning/ultrachat/resolve/main/train_{idx}.jsonl"
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_BASE_DATA_URL = "{_HF_ENDPOINT}/datasets/stingning/ultrachat/resolve/main/train_{idx}.jsonl"
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class UltraChat(datasets.GeneratorBasedBuilder):
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@ -38,7 +40,7 @@ class UltraChat(datasets.GeneratorBasedBuilder):
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)
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def _split_generators(self, dl_manager: datasets.DownloadManager):
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file_paths = [dl_manager.download(_BASE_DATA_URL.format(idx=idx)) for idx in range(10)] # multiple shards
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file_paths = [dl_manager.download(_BASE_DATA_URL.format(_HF_ENDPOINT=_HF_ENDPOINT,idx=idx)) for idx in range(10)] # multiple shards
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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