extract 0 0 0

VMware/open-instruct

published by @VMware

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
8.3K
Last 30 days
139
Likes
46
Size
55.2 MB
Created on HF
2023-07-11
Age
3 years ago

Description

Dataset Card for "open-instruct"

This dataset is a combination of:

Filtered subset of OpenAssistant/oasst1

train split of Mosaic-dolly-hhrlhf (consists of Databrick's dolly-15k dataset and a filtered subset of Anthropic's HH-RLHF).

Filtered subset of conceptofmind/cot_submix_original

Dataset

The dataset consists of 6 columns:

instruction: The natural language instruction without any prompt templates (we extracted them out of the alpaca-format in… See the full description on the dataset page: https://huggingface.co/datasets/VMware/open-instruct.

Tags

task_categories:text-generationlanguage:enlicense:cc-by-3.0size_categories:100K<n<1Mformat:parquetmodality:textlibrary:datasetslibrary:pandaslibrary:mlcroissantlibrary:polarsregion:us

README current version from Hugging Face


dataset_info:
features:

  • name: alpaca_prompt
    dtype: string
  • name: response
    dtype: string
  • name: instruction
    dtype: string
  • name: source
    dtype: string
  • name: task_name
    dtype: string
  • name: template_type
    dtype: string
    splits:
  • name: train
    num_bytes: 125656035
    num_examples: 142622
    download_size: 57912402
    dataset_size: 125656035
    license: cc-by-3.0
    task_categories:
  • text-generation
  • conversational
  • text2text-generation
    language:
  • en
    pretty_name: T
    size_categories:
  • 100K<n<1M

Dataset Card for "open-instruct"

This dataset is a combination of:

  1. Filtered subset of OpenAssistant/oasst1
  2. train split of Mosaic-dolly-hhrlhf (consists of Databrick's dolly-15k dataset and a filtered subset of Anthropic's HH-RLHF).
  3. Filtered subset of conceptofmind/cot_submix_original

Dataset

The dataset consists of 6 columns:

  1. instruction: The natural language instruction without any prompt templates (we extracted them out of the alpaca-format in Mosaic-dolly-hhrlhf)
  2. alpaca_prompt: Alpaca prompt template versions of instruction
  3. response: The response to the instruction
  4. source: Dataset source
  5. task_name
  6. template_type: flan template used (zeroshot or fewshot)

License

  • It is usable for commercial purposes so long as you follow the terms of the license.

Dataset subset licenses:

  • Open-instruct-v1-dolly-hhrlhf-oasst1 (Mosaic/Dolly-HHRLHF + filtered OASST1) - cc by 3.0

Subset of COT SUBMIX (FROM FLAN V2) Zeroshot examples:

  • ESNLI - MIT
  • ECQA - CDLA 1.0 - Sharing
  • Strategy - MIT
  • CREAK - MIT
  • gsmk8 - MIT
  • aqua - MIT
  • qasc - Apache 2.0

Certain categories of material in the dataset include materials from the following sources, licensed under the CC BY-SA 3.0 license:

Wikipedia (various pages) - https://www.wikipedia.org/

  • Copyright © Wikipedia editors and contributors.

Databricks (https://www.databricks.com)

  • Copyright © Databricks

Mosaic ML (https://www.mosaicml.com/)

  • Copyright © Mosaic ML

VMware

  • Copyright © VMware

More Information needed

README history 6 revisions

Every night we snapshot the README of every dataset in the catalog. When the SHA changes we archive the new version and diff it against the last. This is the evolving thought record of the alignment-data field: what the author decided to say about the corpus, and how that framing shifted over time.

  1. 2023-07-12Update README.md9e53e852.4 KB
    Loading...
  2. 2023-07-11Update README.md07f858c2.5 KB
    Loading...
  3. 2023-07-11Update README.md8a80e8d2.4 KB
    Loading...
  4. 2023-07-11Upload README.md with huggingface_hub5af78c4563 B
    Loading...
  5. 2023-07-11Upload data/train-00000-of-00001-c6f4e090ee7100b6.parquet with huggingface_hub94e52660 B
    Loading...
  6. 2023-07-11initial commitcbfc6de0 B
    Loading...

Used by abliterated models none yet

No abliterated models in our catalog have declared this dataset in their YAML metadata yet. This can mean the dataset is used but not declared, is used outside abliteration workflows, or is new. The link will populate automatically as models are indexed.

Related datasets same stage · extract

Read further

Metadata

License
cc-by-3.0

Repository

Download the dataset

0

Copy any of these snippets into your notebook or terminal. All three fetch directly from Hugging Face using your own credentials.

Recommended: datasets library (Python)
from datasets import load_dataset
ds = load_dataset("VMware/open-instruct")
Raw snapshot (Python)
from huggingface_hub import snapshot_download
snapshot_download(repo_id="VMware/open-instruct", repo_type="dataset")
git clone (requires git-lfs)
git clone https://huggingface.co/datasets/VMware/open-instruct
Catalog is the map. Apps are the tools.

Run models on your own machine, not in the cloud.

Every model page has an "Open in Abliteration" button that hands the model directly to the first-party desktop client, at the quantization your rig can actually run. No API keys, no subscription, no prompt leakage.

Open in Abliteration