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ai2-adapt-dev/hh-rlhf-helpful

Name: ai2-adapt-dev/hh-rlhf-helpful
Creator: ai2-adapt-dev
Published: 2024-08-28T21:10:10

published by @ai2-adapt-dev

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads

550

Last 30 days

Likes

Size

57.9 MB

Created on HF

2024-08-28

Age

2 years ago

README current version from Hugging Face

dataset_info:
features:

name: chosen
list:
- name: content
  dtype: string
- name: role
  dtype: string
name: rejected
list:
- name: content
  dtype: string
- name: role
  dtype: string
name: messages
list:
- name: content
  dtype: string
- name: role
  dtype: string
  splits:
name: train
num_bytes: 103900305.33801757
num_examples: 43713
name: test
num_bytes: 5612202.630841121
num_examples: 2343
download_size: 60710961
dataset_size: 109512507.96885869
configs:
config_name: default
data_files:
- split: train
  path: data/train-*
- split: test
  path: data/test-*

README history 5 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.

2024-08-28Upload create_dataset.py with huggingface_hub2e9c814690 B
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2024-08-28Upload dataset50b20b6690 B
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2024-08-28Upload create_dataset.py with huggingface_hub9b1805f665 B
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2024-08-28Upload dataset86fb5e0665 B
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2024-08-28initial commita76d55a0 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.

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Non-English abliteration communities

How Chinese, Russian, Japanese, and Korean practitioners build extraction pairs.

Repository

DIR data 2 files FILE .gitattributes FILE create_dataset.py FILE README.md

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

Download the dataset

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("ai2-adapt-dev/hh-rlhf-helpful")

Raw snapshot (Python)

from huggingface_hub import snapshot_download
snapshot_download(repo_id="ai2-adapt-dev/hh-rlhf-helpful", repo_type="dataset")

git clone (requires git-lfs)

git clone https://huggingface.co/datasets/ai2-adapt-dev/hh-rlhf-helpful

Browse repository on Hugging Face ->