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OpenMOSS-Team/moss-002-sft-data

published by @OpenMOSS-Team

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
7.7K
Last 30 days
342
Likes
96
Size
2.1 GB
Created on HF
2023-04-20
Age
3 years ago

Description

Dataset Card for "moss-002-sft-data"

Dataset Summary

An open-source conversational dataset that was used to train MOSS-002. The user prompts are extended based on a small set of human-written seed prompts in a way similar to Self-Instruct. The AI responses are generated using text-davinci-003. The user prompts of en_harmlessness are from Anthropic red teaming data.

Data Splits

name

# samples

en_helpfulness.json

419049

en_honesty.json… See the full description on the dataset page: https://huggingface.co/datasets/OpenMOSS-Team/moss-002-sft-data.

Tags

task_categories:text-generationlanguage:enlanguage:zhlicense:cc-by-4.0size_categories:1M<n<10Mformat:jsonmodality:tabularmodality:textlibrary:datasetslibrary:dasklibrary:mlcroissantarxiv:2212.10560region:us

README current version from Hugging Face

license: cc-by-4.0
task_categories:

  • conversational
  • text-generation
    language:
  • en
  • zh
    size_categories:
  • 1M<n<10M

Dataset Card for "moss-002-sft-data"

Dataset Description

Dataset Summary

An open-source conversational dataset that was used to train MOSS-002. The user prompts are extended based on a small set of human-written seed prompts in a way similar to Self-Instruct. The AI responses are generated using text-davinci-003. The user prompts of en_harmlessness are from Anthropic red teaming data.

Data Splits

name # samples
en_helpfulness.json 419049
en_honesty.json 112580
en_harmlessness.json 38873
zh_helpfulness.json 447750
zh_honesty.json 142885

README history 7 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. 2023-04-20Update README.mdd530c921.1 KB
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  2. 2023-04-20Upload zh_honesty.json with huggingface_huba664f3827 B
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  3. 2023-04-20Upload zh_helpfulness.json with huggingface_hubf2d4e8027 B
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  4. 2023-04-20Upload en_honesty.json with huggingface_huba052c0a27 B
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  5. 2023-04-20Upload en_helpfulness.json with huggingface_hub80b4e2227 B
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  6. 2023-04-20Upload en_harmlessness.json with huggingface_hubcdc89df27 B
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  7. 2023-04-20initial commit98af05d27 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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Read further

Community best practices (architecture)
4 rules for MoE, hybrid SSM, FP8 requantization, and Gemma quirks.
The six workflow stages
What misc is doing more work than its name suggests.
Beyond English: multilingual corpora
The four language communities and their workarounds.
Non-English abliteration communities
Deep dive: huihui-ai, layer-window, slop-framing, CJK tokenizer fixes.

Metadata

License
cc-by-4.0

Repository

FILE .gitattributes FILE en_harmlessness.json FILE en_helpfulness.json FILE en_honesty.json FILE README.md FILE zh_helpfulness.json FILE zh_honesty.json

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("OpenMOSS-Team/moss-002-sft-data")
Raw snapshot (Python) 
from huggingface_hub import snapshot_download
snapshot_download(repo_id="OpenMOSS-Team/moss-002-sft-data", repo_type="dataset")
git clone (requires git-lfs) 
git clone https://huggingface.co/datasets/OpenMOSS-Team/moss-002-sft-data
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