datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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.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-curated-multilingual
Dataset Card for "databricks-dolly-15k-curated-multilingual"
A curated and multilingual version of the Databricks Dolly instructions dataset. It includes a programmatically and manually corrected version of the original en dataset. See below.
STATUS:
Currently, the original Dolly v2 English version has been curated combining automatic processing and collaborative human curation using Argilla (~400 records have been manually edited and fixed). The following graph shows a summary… See the full description on the dataset page: https://huggingface.co/datasets/argilla/databricks-dolly-15k-curated-multilingual.databricksdatabricks-dolly-15k-chinese
Dataset Summary
🏡🏡🏡🏡Fine-tune Dataset:中文数据集🏡🏡🏡🏡
😀😀😀😀😀😀😀😀 这个数据集是databricks/databricks-dolly-15k的中文版本，是直接翻译过来，没有经过人为检查语法。 对databricks/databricks-dolly-15k的描述，请看他的dataset card。
😀😀😀😀😀😀😀😀 This data set is the Chinese version of databricks/databricks-dolly-15k, which is directly translated without human-checked grammar. For a description of databricks/databricks-dolly-15k, see its dataset card.
ChatML-databricks-dolly-15kdatabricks/databricks-dolly-15k in ChatML format.
Python code used for conversion:
from datasets import load_dataset
import pandas
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained(
pretrained_model_name_or_path="Felladrin/Llama-160M-Chat-v1"
)
dataset = load_dataset("databricks/databricks-dolly-15k", split="train")
def format(columns):
instruction = columns["instruction"].strip()
context = columns["context"].strip()
response =… See the full description on the dataset page: https://huggingface.co/datasets/Felladrin/ChatML-databricks-dolly-15k.databricks-sft-15kdatabricks_dolly_15k
Databricks Dolly task samples
Standalone task subsets derived from
databricks/databricks-dolly-15k at
revision bdd27f4d94b9c1f951818a7da7fd7aeea5dbff1a:
general_qa (source category: general_qa)
open_qa (source category: open_qa)
closed_qa (source category: closed_qa)
brainstorm (source category: brainstorming)
classify (source category: classification)
extract_information (source category: information_extraction)
summarize (source category: summarization)
creative_writing… See the full description on the dataset page: https://huggingface.co/datasets/Alberto1231/databricks_dolly_15k.databricks-dolly-15k-esTranslated with googletrans==3.1.0a0 from original dataset
*part of the data (up to 600) was lost during the translation
license: apache-2.0
databricks-dolly-15k
Databricks-dolly
This is a cleansed version of databricks/databricks-dolly-15k
Usage
from datasets import load_dataset
dataset = load_dataset("Sharathhebbar24/databricks-dolly-15k", split="train")
SFT_databricks_dolly_15k
Preparing Your Dataset
Once you’ve decided that fine-tuning is the best approach—after optimizing your prompt as much as possible and identifying remaining model issues—you’ll need to prepare training data. Start by creating a diverse set of example conversations that mirror those the model will handle during production.
Each example should follow this structure below, consisting of a list of messages. Each message must include a role, content, and an optional name. Make sure some… See the full description on the dataset page: https://huggingface.co/datasets/GreenNode/SFT_databricks_dolly_15k.textGen-databricks-dollydatabricks-dolly-1k
Databricks Dolly 1k
1092 instruction examples taken from the original databricks/databricks-dolly-15k.
Filtered to open/closed/general QA category
Ready to plug straight into SFTTrainer, Unsloth, Llama-factory etc
Example
### Instruction:
When did Virgin Australia start operating?
### Context:
Virgin Australia, the trading name of Virgin Australia Airlines Pty Ltd ...
### Response:
Virgin Australia commenced services on 31 August 2000 as Virgin Blue, with two aircraft… See the full description on the dataset page: https://huggingface.co/datasets/MagicaNeko/databricks-dolly-1k.