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VMware/open-instruct-v1-oasst-dolly-hhrlhf

published by @VMware

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
3.2K
Last 30 days
49
Likes
20
Size
31.7 MB
Created on HF
2023-05-10
Age
3 years ago

Description

Dataset Card for "open-instruct-v1-oasst-dolly-hhrlhf"

This dataset is a combination of:

Filtered subset ofOpenAssistant/oasst1

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

Dataset

The dataset consists of 3 columns:

instruction: The natural language instruction without any prompt templates (we extracted them out of the alpaca-format in Mosaic-dolly-hhrlhf)

alpaca_prompt: Alpaca… See the full description on the dataset page: https://huggingface.co/datasets/VMware/open-instruct-v1-oasst-dolly-hhrlhf.

Tags

language:ensize_categories:10K<n<100Kformat:parquetmodality:textlibrary:datasetslibrary:pandaslibrary:mlcroissantlibrary:polarsregion:us

README current version from Hugging Face

language: en
dataset_info:
features:

  • name: 'Unnamed: 0'
    dtype: int64
  • name: alpaca_prompt
    dtype: string
  • name: response
    dtype: string
  • name: instruction
    dtype: string
    splits:
  • name: train
    num_bytes: 60252132
    num_examples: 62971
    download_size: 33232110
    dataset_size: 60252132

Dataset Card for "open-instruct-v1-oasst-dolly-hhrlhf"

This dataset is a combination of:

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

Dataset

The dataset consists of 3 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

License

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

  • 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 9 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. 2023-07-13HuggyLingo Bot: Add language information to your dataset (#1)664b6531.7 KB
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  2. 2023-06-21Update README.mdb3161951.7 KB
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  3. 2023-06-10Update README.md84a21571.7 KB
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  4. 2023-06-08Update README.md945b35e1.7 KB
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  5. 2023-05-12Update README.md8b4f5391.7 KB
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  6. 2023-05-10Update README.md48478c41.4 KB
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  7. 2023-05-10Upload README.md with huggingface_hubf1c0411509 B
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  8. 2023-05-10Upload data/train-00000-of-00001-c50510153c133a3a.parquet with huggingface_hubacc956f0 B
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  9. 2023-05-10initial commit232c9600 B
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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.

Community discussions 1 thread · 1 comments

Threads posted by the community on Hugging Face: bug reports, questions about usage, pull requests on the README, license clarifications. Click any thread to expand and read the full conversation inline. Newest first.

  1. 2023-07-13PRHuggyLingo Bot: Add language information to your datasetmerged1 💬#1
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Repository

DIR data FILE .gitattributes FILE README.md

File contents live on Hugging Face. Click a file or folder to open it there.

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-v1-oasst-dolly-hhrlhf")
Raw snapshot (Python) 
from huggingface_hub import snapshot_download
snapshot_download(repo_id="VMware/open-instruct-v1-oasst-dolly-hhrlhf", repo_type="dataset")
git clone (requires git-lfs) 
git clone https://huggingface.co/datasets/VMware/open-instruct-v1-oasst-dolly-hhrlhf
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