Summary

databricks-dolly-15k is an open source dataset of instruction-following records generated by thousands of Databricks employees in several of the behavioral categories outlined in the InstructGPT paper, including brainstorming, classification, closed QA, generation, information extraction, open QA, and summarization. This dataset can be used for any purpose, whether academic or commercial, under the terms of the Creative Commons Attribution-ShareAlike 3.0 Unported… See the full description on the dataset page: https://huggingface.co/datasets/databricks/databricks-dolly-15k.

This dataset was created by automatically translating "databricks-dolly-15k" into Japanese.

Summary

databricks-dolly-15k-cleanset can be used to produced CLEANed up versions of the popular databricks-dolly-15k dataSET, which was used to fine-tune the Dolly 2.0. The original databricks-dolly-15k contains 15,000 human-annotated instruction-response pairs covering various categories. However, there are many low-quality responses, incomplete/vague prompts, and other problematic text lurking in the dataset (as with for all real-world instruction tuning datasets). We ran… See the full description on the dataset page: https://huggingface.co/datasets/Cleanlab/databricks-dolly-15k-cleanset.

Dataset

This dataset was created by Prathamesh Sonawane

Contents

Dataset

This dataset was created by Beyza Coban

Released under Apache 2.0

Contents

databricks-dolly-15k-ja

This repository provides an instruction tuning dataset developed by LLM-jp, a collaborative project launched in Japan. This dataset is a Japanese translation of databricks-dolly-15k using DeepL.

  Send Questions to

llm-jp(at)nii.ac.jp

  Model Card Authors

The names are listed in alphabetical order. Hirokazu Kiyomaru, Hiroshi Matsuda, Jun Suzuki, Namgi Han, Saku Sugawara, Shota Sasaki, Shuhei Kurita, Taishi Nakamura, Takashi Kodama, Takumi… See the full description on the dataset page: https://huggingface.co/datasets/llm-jp/databricks-dolly-15k-ja.

Dataset

This dataset was created by Caleb Klinger

Released under CC0: Public Domain

Contents

databricks-dolly-15k is a corpus of more than 15,000 records generated by thousands of Databricks employees to enable large language models to exhibit the magical interactivity of ChatGPT. Databricks employees were invited to create prompt / response pairs in each of eight different instruction categories, including the seven outlined in the InstructGPT paper, as well as an open-ended free-form category. The contributors were instructed to avoid using information from any source on the web with the exception of Wikipedia (for particular subsets of instruction categories), and explicitly instructed to avoid using generative AI in formulating instructions or responses. Examples of each behavior were provided to motivate the types of questions and instructions appropriate to each category. Halfway through the data generation process, contributors were given the option of answering questions posed by other contributors. They were asked to rephrase the original question and only select questions they could be reasonably expected to answer correctly. For certain categories contributors were asked to provide reference texts copied from Wikipedia. Reference text (indicated by the context field in the actual dataset) may contain bracketed Wikipedia citation numbers (e.g. [42]) which we recommend users remove for downstream applications.

Guidelines

In this dataset, you will find a collection of records that show a category, an instruction, a context and a response to that instruction. The aim of the project is to correct the instructions, intput and responses to make sure they are of the highest quality and that they match the task category that they belong to. All three texts should be clear and include real information. In addition, the response should be as complete but concise as possible. To curate the dataset… See the full description on the dataset page: https://huggingface.co/datasets/argilla/databricks-dolly-15k-curated-en.

Dataset Card for "databricks-databricks-dolly-15k"

More Information needed

This is a Non-IID split version of databricks/databricks-dolly-15k.

marcov/instruct-rl-databricks-dolly-15k dataset hosted on Hugging Face and contributed by the HF Datasets community

Korea-MES/databricks-dolly-15k dataset hosted on Hugging Face and contributed by the HF Datasets community

Dataset Card for "databricks-dolly-15k-chatml"

  Dataset Summary

This dataset has been created by Re:cast AI to transform the existing dataset databricks/databricks-dolly-15k into a chatml friendly format for use in SFT tasks with pretrained models.

  Dataset Structure

messages = [ { "content": "You are an expert Q&A system that is trusted around the world. You always... etc.", "role": "system" }, { "content": "(Optional) Context information is… See the full description on the dataset page: https://huggingface.co/datasets/recastai/databricks-dolly-15k-chatml.

Summary

This is a Thai 🇹🇭-instructed dataset translated from databricks-dolly-15k using Google Cloud Translation. databricks-dolly-15k is an open-source dataset of instruction-following records generated by thousands of Databricks employees in several behavioral categories outlined in the InstructGPT paper, including brainstorming, classification, closed QA, generation, information extraction, open QA, and summarization. This dataset can be used for any purpose, whether academic… See the full description on the dataset page: https://huggingface.co/datasets/Thaweewat/databricks-dolly-15k-th.

Dataset Card for "databricks-dolly-15k-llama"

More Information needed

andrewbai/databricks-dolly-15k dataset hosted on Hugging Face and contributed by the HF Datasets community

vsevolodl/databricks-dolly-15k-sum dataset hosted on Hugging Face and contributed by the HF Datasets community

edition_0016_argilla-databricks-dolly-15k-curated-en-readymade

A Readymade by TheFactoryX

  Original Dataset

argilla/databricks-dolly-15k-curated-en

  Process

This dataset is a "readymade" - inspired by Marcel Duchamp's concept of taking everyday objects and recontextualizing them as art. What we did:

Selected the original dataset from Hugging Face Shuffled each column independently Destroyed all row-wise relationships Preserved structure, removed meaning

The… See the full description on the dataset page: https://huggingface.co/datasets/TheFactoryX/edition_0016_argilla-databricks-dolly-15k-curated-en-readymade.

This is a checkpoint of the databricks-dolly-15k dataset