databricks
databricks-dolly-v2-3bdistilgpt2-finetuned-databricks-GGUFrobertvacareanu_-_instruct-rl-Qwen2.5-1.5B-databricks-dolly-15k-ggufrobertvacareanu_-_instruct-rl-Qwen2.5-0.5B-databricks-dolly-15k-ggufdatabricks_-_dbrx-instruct-ggufPranjalya_-_SmolLM2-FT-databricks-dolly-15k-ggufmarcov_-_Qwen2.5-1.5B-Instruct-databricks-dolly-15k-ggufkarasu-databricks-dolly-v0.1-GGUF
databricks-dolly-15k-curated-en
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.databricks-dolly-15k
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.officeqa
OfficeQA
Dataset Summary
OfficeQA is a grounded reasoning benchmark by Databricks for evaluating model and agent performance on end-to-end reasoning over real-world documents.
The benchmark consists of question–answer pairs that require reasoning over historical U.S. Treasury Bulletin documents (1939–2025), which contain dense financial tables, charts, and narrative text. OfficeQA is designed to test retrieval, tool use, and multi-step reasoning in… See the full description on the dataset page: https://huggingface.co/datasets/databricks/officeqa.databricks_dolly_15k
Dataset Card for Dolly_15K
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… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceH4/databricks_dolly_15k.officeqa-pro-v2
OfficeQA Pro v2
Dataset Summary
OfficeQA Pro v2 is a grounded reasoning benchmark by Databricks for evaluating model and agent performance on end-to-end reasoning over real-world documents.
The benchmark consists of question–answer pairs that require reasoning over two centuries of U.S. Federal Accounts of Receipts and Expenditures reporting (1793–2024) — Combined Statements of Receipts, Outlays, and Balances of the United States Government, together with earlier… See the full description on the dataset page: https://huggingface.co/datasets/databricks/officeqa-pro-v2.databricks-dolly-15k-ja
This dataset was created by automatically translating "databricks-dolly-15k" into Japanese.This dataset is licensed under CC-BY-SA-3.0
Last Update : 2023-05-11
databricks-dolly-15k-jahttps://github.com/kunishou/databricks-dolly-15k-jadatabricks-dolly-15khttps://github.com/databrickslabs/dolly/tree/master/data