add orca_dpo_pairs dataset

data/belle_multiturn/belle_multiturn.py

@@ -2,6 +2,7 @@ import os
 import json
 import datasets
 
+
 _HF_ENDPOINT = os.getenv("HF_ENDPOINT", "https://huggingface.co")
 
 _DESCRIPTION = "BELLE multiturn chat dataset."
@@ -15,9 +16,9 @@ _CITATION = """\
 }
 """
 
-_HOMEPAGE = f"{_HF_ENDPOINT}/datasets/BelleGroup/multiturn_chat_0.8M"
+_HOMEPAGE = "{}/datasets/BelleGroup/multiturn_chat_0.8M".format(_HF_ENDPOINT)
 _LICENSE = "gpl-3.0"
-_URL = f"{_HF_ENDPOINT}/datasets/BelleGroup/multiturn_chat_0.8M/resolve/main/multiturn_chat_0.8M.json"
+_URL = "{}/datasets/BelleGroup/multiturn_chat_0.8M/resolve/main/multiturn_chat_0.8M.json".format(_HF_ENDPOINT)
 
 
 class BelleMultiturn(datasets.GeneratorBasedBuilder):

data/dataset_info.json

@@ -220,6 +220,14 @@
     "ms_hub_url": "AI-ModelScope/WizardLM_evol_instruct_V2_196k",
     "formatting": "sharegpt"
   },
+  "glaive_toolcall_100k": {
+    "hf_hub_url": "hiyouga/glaive-function-calling-v2-sharegpt",
+    "formatting": "sharegpt",
+    "columns": {
+      "messages": "conversations",
+      "tools": "tools"
+    }
+  },
   "cosmopedia": {
     "hf_hub_url": "HuggingFaceTB/cosmopedia",
     "columns": {
@@ -295,6 +303,16 @@
     "file_sha1": "515b18ed497199131ddcc1af950345c11dc5c7fd",
     "ranking": true
   },
+  "orca_rlhf": {
+    "file_name": "orca_rlhf.json",
+    "file_sha1": "acc8f74d16fd1fc4f68e7d86eaa781c2c3f5ba8e",
+    "ranking": true,
+    "columns": {
+      "prompt": "question",
+      "response": "answer",
+      "system": "system"
+    }
+  },
   "nectar_rm": {
     "hf_hub_url": "mlinmg/RLAIF-Nectar",
     "ms_hub_url": "AI-ModelScope/RLAIF-Nectar",

data/hh_rlhf_en/hh_rlhf_en.py

@@ -3,15 +3,12 @@ import json
 import datasets
 from typing import List
 
-_HF_ENDPOINT = os.getenv("_HF_ENDPOINT", "https://huggingface.co")
-
+_HF_ENDPOINT = os.getenv("HF_ENDPOINT", "https://huggingface.co")
 _DESCRIPTION = "Human preference data about helpfulness and harmlessness."
-
 _CITATION = ""
-
-_HOMEPAGE = f"{_HF_ENDPOINT}/datasets/Anthropic/hh-rlhf"
+_HOMEPAGE = "{}/datasets/Anthropic/hh-rlhf".format(_HF_ENDPOINT)
 _LICENSE = "mit"
-_URL = f"{_HF_ENDPOINT}/datasets/Anthropic/hh-rlhf/resolve/main/"
+_URL = "{}/datasets/Anthropic/hh-rlhf/resolve/main/".format(_HF_ENDPOINT)
 _URLS = {
     "train": [
         _URL + "harmless-base/train.jsonl.gz",

data/ultra_chat/ultra_chat.py

@@ -3,7 +3,7 @@ import json
 import datasets
 from typing import List
 
-_HF_ENDPOINT = os.getenv("_HF_ENDPOINT", "https://huggingface.co")
+_HF_ENDPOINT = os.getenv("HF_ENDPOINT", "https://huggingface.co")
 
 _DESCRIPTION = "UltraChat: Large-scale, Informative, and Diverse Multi-round Dialogue Data."
 
@@ -18,9 +18,9 @@ _CITATION = """\
 }
 """
 
-_HOMEPAGE = f"{_HF_ENDPOINT}/datasets/stingning/ultrachat"
+_HOMEPAGE = "{}/datasets/stingning/ultrachat".format(_HF_ENDPOINT)
 _LICENSE = "cc-by-nc-4.0"
-_BASE_DATA_URL = "{_HF_ENDPOINT}/datasets/stingning/ultrachat/resolve/main/train_{idx}.jsonl"
+_BASE_DATA_URL = "{}/datasets/stingning/ultrachat/resolve/main/train_{{idx}}.jsonl".format(_HF_ENDPOINT)
 
 
 class UltraChat(datasets.GeneratorBasedBuilder):
@@ -40,7 +40,7 @@ class UltraChat(datasets.GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager: datasets.DownloadManager):
-        file_paths = [dl_manager.download(_BASE_DATA_URL.format(_HF_ENDPOINT=_HF_ENDPOINT,idx=idx)) for idx in range(10)] # multiple shards
+        file_paths = [dl_manager.download(_BASE_DATA_URL.format(idx=idx)) for idx in range(10)] # multiple shards
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,