datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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.databricks_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
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-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.databricks-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.textGen-databricks-dollyDatabricks-Dolly-6k
Databricks-Dolly-8k
The resulting dataset contains 6000 samples of the databricks/databricks-dolly-15k dataset.
This split of an even smaller subset is provided for very fast experimentation and evaluation of models when computational resources are highly limited or for quick prototyping.
Dataset Structure
The dataset is provided as a DatasetDict with the following splits:
train: Contains 6000 samples.
Each split contains the following features, identical to the… See the full description on the dataset page: https://huggingface.co/datasets/Vishva007/Databricks-Dolly-6k.Databricks-Dolly-4k
Databricks-Dolly-4k
The resulting dataset contains 4000 samples of the databricks/databricks-dolly-15k dataset.
This split of an even smaller subset is provided for very fast experimentation and evaluation of models when computational resources are highly limited or for quick prototyping.
Dataset Structure
The dataset is provided as a DatasetDict with the following splits:
train: Contains 4000 samples.
Each split contains the following features, identical to the… See the full description on the dataset page: https://huggingface.co/datasets/Vishva007/Databricks-Dolly-4k.Databricks-Dolly-8k
Databricks-Dolly-8k
The resulting dataset contains 8000 samples of the databricks/databricks-dolly-15k dataset.
This split of an even smaller subset is provided for very fast experimentation and evaluation of models when computational resources are highly limited or for quick prototyping.
Dataset Structure
The dataset is provided as a DatasetDict with the following splits:
train: Contains 8000 samples.
Each split contains the following features, identical to the… See the full description on the dataset page: https://huggingface.co/datasets/Vishva007/Databricks-Dolly-8k.
