# Dataset Card for "instruction_merge_set"

## 本数据集由以下数据集构成：

| 数据(id in the merged set) | Hugging face 地址 | notes |
| --- | --- | --- |
| OIG (unified-任务名称)  15k | https://huggingface.co/datasets/laion/OIG | Open Instruction Generalist Dataset |
| Dolly  databricks-dolly-15k  | https://huggingface.co/datasets/databricks/databricks-dolly-15k | an open-source dataset of instruction-following records generated by thousands of Databricks employees in several of the behavioral categories |
| UltraChat  | https://huggingface.co/datasets/stingning/ultrachat | multi-round dialogue data  |
| Camel   | https://huggingface.co/datasets/camel-ai/ai_society | 25K conversations between two gpt-3.5-turbo agents.   |
| camel (同上) | https://github.com/camel-ai/camel |  |
| ChatDoctor icliniq-15k HealthCareMagic-200k | https://github.com/Kent0n-Li/ChatDoctor | 200k real conversations between patients and doctors from HealthCareMagic.com 15k real conversations between patients and doctors from iciniq-10k |
| Dolly  | https://github.com/databrickslabs/dolly |  |
| GPT4ALL | https://github.com/nomic-ai/gpt4all |  |
| GPT-4-LLM comparision_data_b alpaca_gpt4_data_zh comparision_data_a alpaca_gpt4_data 5k  | https://github.com/Instruction-Tuning-with-GPT-4/GPT-4-LLM | English Instruction-Following Data generated by GPT-4 using Alpaca prompts for fine-tuning LLMs. Chinese Instruction-Following Data generated by GPT-4 using Chinese prompts translated from Alpaca by ChatGPT. Comparison Data ranked by GPT-4 to train reward models. Answers on Unnatural Instructions Data from GPT-4 to quantify the gap between GPT-4 and instruction-tuned models at scale. |
| GuanacoDataset guanaco_chat_all-utf8 guanaco_non_chat-utf8 paper_answers-utf8 general_ans-utf8 general_questions-utf8 paper_questions-utf8 30k | https://huggingface.co/datasets/JosephusCheung/GuanacoDataset | The dataset for the Guanaco model is designed to enhance the multilingual capabilities and address various linguistic tasks. It builds upon the 175 tasks from the Alpaca model by providing rewrites of seed tasks in different languages and adding new tasks specifically designed for English grammar analysis, natural language understanding, cross-lingual self-awareness, and explicit content recognition.  The Paper/General-QA dataset is a collection of questions and answers constructed for AI-generated papers or general texts in English, Chinese, Japanese, and German. |
| HC3 ALL | https://huggingface.co/datasets/Hello-SimpleAI/HC3 | human-ChatGPT comparison datasets |
| instinwild instinwild_en instinwild_ch 5k  | https://huggingface.co/datasets/QingyiSi/Alpaca-CoT/tree/main/instinwild | Instruction-Finetuning Dataset Collection (Alpaca-CoT)  |
| Instruct-to-Code  | https://huggingface.co/datasets/Graverman/Instruct-to-Code |   |
| ShareGPT90K sg_90k_part2 sg_90k_part1  | https://huggingface.co/datasets/RyokoAI/ShareGPT52K | 90,000 conversations scraped via the ShareGPT API before it was shut down. These conversations include both user prompts and responses from OpenAI's ChatGPT. |
| UltraChat ultrachat_material_release_230412 ultrachat_release_230407 | https://github.com/thunlp/UltraChat |  |
| wealth-alpaca-lora final_dataset_clean 4.3k | https://www.kaggle.com/code/gbhacker23/wealth-alpaca-lora  | combination of Stanford's Alpaca (https://github.com/tatsu-lab/stanford_alpaca) and FiQA (https://sites.google.com/view/fiqa/) with another 1.3k pairs custom generated using GPT3.5, 有instruction |
| Alpaca alpaca_data 5k | https://github.com/tatsu-lab/stanford_alpaca | instruct-tuning |
| Baize alpaca_chat_data medical_chat_data quora_chat_data stack_overflow_chat_data | https://github.com/project-baize/baize-chatbot | instruction-following data we used for fine-tuning the Alpaca model.  |
| botbots Reasoning flight_bookings medical_appointments travel_agency restaurants_mixed real_estate car_dealership  home_maintenance,  job_interview     'insurance_consultation': 16,      'hotels': 400,      'tech_support': 32,      'car_rentals': 32,      'pet_care': 48,      'restaurants': 200,      'legal_consultation': 16,      'event_tickets': 240,      'fitness_personal_training': 16,      'scientific_problems': 100 | https://github.com/radi-cho/botbots | A dataset consisting of dialogues between two instances of ChatGPT (gpt-3.5-turbo). The CLI commands and dialogue prompts themselves have been written by GPT-4. The dataset covers a wide range of contexts (questions and answers, arguing and reasoning, task-oriented dialogues) and downstream tasks (e.g., hotel reservations, medical advice). |
| ChatAlpaca chatalpaca_data_10k | https://github.com/cascip/ChatAlpaca | a chat dataset, multi-turn instruction-following conversations.  |
| DERA train | https://github.com/curai/curai-research/tree/main/DERA | The following repository contains the open-ended question-answering version of MedQA. |
| GPTeacher Toolformer-dedupe-only-dataset roleplay-simple-deduped-roleplay-dataset  gpt4-instruct-dedupe-only-dataset | https://github.com/teknium1/GPTeacher | A collection of modular datasets generated by GPT-4, General-Instruct - Roleplay-Instruct - Code-Instruct - and Toolformer  |
| OpenAGI  | https://github.com/agiresearch/OpenAGI |  |
| presto | https://github.com/google-research-datasets/presto | A Multilingual Dataset for Parsing Realistic Task-Oriented Dialogs |

region:us
{"dataset_info": {"features": [{"name": "id", "dtype": "string"}, {"name": "conversations", "list": [{"name": "from", "dtype": "string"}, {"name": "value", "dtype": "string"}]}, {"name": "instruction", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 13444870155, "num_examples": 10077297}], "download_size": 3542585235, "dataset_size": 13444870155}}
TAGS
#region-us 

Dataset Card for "instruction\_merge\_set"
==========================================


本数据集由以下数据集构成：
-------------


数据(id in the merged set): OIG (unified-任务名称) 15k, Hugging face 地址: URL, notes: Open Instruction Generalist Dataset
数据(id in the merged set): Dolly databricks-dolly-15k, Hugging face 地址: URL, notes: an open-source dataset of instruction-following records generated by thousands of Databricks employees in several of the behavioral categories
数据(id in the merged set): UltraChat, Hugging face 地址: URL, notes: multi-round dialogue data
数据(id in the merged set): Camel, Hugging face 地址: URL, notes: 25K conversations between two gpt-3.5-turbo agents.
数据(id in the merged set): camel (同上), Hugging face 地址: URL, notes: 
数据(id in the merged set): ChatDoctor icliniq-15k HealthCareMagic-200k, Hugging face 地址: URL, notes: 200k real conversations between patients and doctors from URL 15k real conversations between patients and doctors from iciniq-10k
数据(id in the merged set): Dolly, Hugging face 地址: URL, notes: 
数据(id in the merged set): GPT4ALL, Hugging face 地址: URL, notes: 
数据(id in the merged set): GPT-4-LLM comparision\_data\_b alpaca\_gpt4\_data\_zh comparision\_data\_a alpaca\_gpt4\_data 5k, Hugging face 地址: URL, notes: English Instruction-Following Data generated by GPT-4 using Alpaca prompts for fine-tuning LLMs. Chinese Instruction-Following Data generated by GPT-4 using Chinese prompts translated from Alpaca by ChatGPT. Comparison Data ranked by GPT-4 to train reward models. Answers on Unnatural Instructions Data from GPT-4 to quantify the gap between GPT-4 and instruction-tuned models at scale.
数据(id in the merged set): GuanacoDataset guanaco\_chat\_all-utf8 guanaco\_non\_chat-utf8 paper\_answers-utf8 general\_ans-utf8 general\_questions-utf8 paper\_questions-utf8 30k, Hugging face 地址: URL, notes: The dataset for the Guanaco model is designed to enhance the multilingual capabilities and address various linguistic tasks. It builds upon the 175 tasks from the Alpaca model by providing rewrites of seed tasks in different languages and adding new tasks specifically designed for English grammar analysis, natural language understanding, cross-lingual self-awareness, and explicit content recognition. The Paper/General-QA dataset is a collection of questions and answers constructed for AI-generated papers or general texts in English, Chinese, Japanese, and German.
数据(id in the merged set): HC3 ALL, Hugging face 地址: URL, notes: human-ChatGPT comparison datasets
数据(id in the merged set): instinwild instinwild\_en instinwild\_ch 5k, Hugging face 地址: URL, notes: Instruction-Finetuning Dataset Collection (Alpaca-CoT)
数据(id in the merged set): Instruct-to-Code, Hugging face 地址: URL, notes: 
数据(id in the merged set): ShareGPT90K sg\_90k\_part2 sg\_90k\_part1, Hugging face 地址: URL, notes: 90,000 conversations scraped via the ShareGPT API before it was shut down. These conversations include both user prompts and responses from OpenAI's ChatGPT.
数据(id in the merged set): UltraChat ultrachat\_material\_release\_230412 ultrachat\_release\_230407, Hugging face 地址: URL, notes: 
数据(id in the merged set): wealth-alpaca-lora final\_dataset\_clean 4.3k, Hugging face 地址: URL, notes: combination of Stanford's Alpaca (URL and FiQA (URL with another 1.3k pairs custom generated using GPT3.5, 有instruction
数据(id in the merged set): Alpaca alpaca\_data 5k, Hugging face 地址: URL, notes: instruct-tuning
数据(id in the merged set): Baize alpaca\_chat\_data medical\_chat\_data quora\_chat\_data stack\_overflow\_chat\_data, Hugging face 地址: URL, notes: instruction-following data we used for fine-tuning the Alpaca model.
数据(id in the merged set): botbots Reasoning flight\_bookings medical\_appointments travel\_agency restaurants\_mixed real\_estate car\_dealership home\_maintenance, job\_interview 'insurance\_consultation': 16, 'hotels': 400, 'tech\_support': 32, 'car\_rentals': 32, 'pet\_care': 48, 'restaurants': 200, 'legal\_consultation': 16, 'event\_tickets': 240, 'fitness\_personal\_training': 16, 'scientific\_problems': 100, Hugging face 地址: URL, notes: A dataset consisting of dialogues between two instances of ChatGPT (gpt-3.5-turbo). The CLI commands and dialogue prompts themselves have been written by GPT-4. The dataset covers a wide range of contexts (questions and answers, arguing and reasoning, task-oriented dialogues) and downstream tasks (e.g., hotel reservations, medical advice).
数据(id in the merged set): ChatAlpaca chatalpaca\_data\_10k, Hugging face 地址: URL, notes: a chat dataset, multi-turn instruction-following conversations.
数据(id in the merged set): DERA train, Hugging face 地址: URL, notes: The following repository contains the open-ended question-answering version of MedQA.
数据(id in the merged set): GPTeacher Toolformer-dedupe-only-dataset roleplay-simple-deduped-roleplay-dataset gpt4-instruct-dedupe-only-dataset, Hugging face 地址: URL, notes: A collection of modular datasets generated by GPT-4, General-Instruct - Roleplay-Instruct - Code-Instruct - and Toolformer
数据(id in the merged set): OpenAGI, Hugging face 地址: URL, notes: 
数据(id in the merged set): presto, Hugging face 地址: URL, notes: A Multilingual Dataset for Parsing Realistic Task-Oriented Dialogs



TAGS
#region-us 

passage: TAGS
#region-us 
