Get the app
heal 0 0 0

adamo1139/toxic-dpo-natural-v1

published by @adamo1139

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
378
Last 30 days
14
Likes
1
Size
2.4 MB
Created on HF
2024-04-02
Age
2 years ago

Description

I wanted to improve on unalignment/toxic-dpo-v0.1 by having more natural-sounding responses and less numbered lists. I used original prompts plus added around 40 unique new prompts related to medicine.

Issues:

there are some prompts that result in the model saying silly braindead things like adding up sugar blood level to blood pressure or going into thesaurus mode, will need fixes.

IDs of prompts are not unique, bear that in mind.

Tags

license:othersize_categories:n<1Kformat:jsonmodality:textlibrary:datasetslibrary:pandaslibrary:mlcroissantlibrary:polarsregion:usnot-for-all-audiences

README current version from Hugging Face

license: other
license_name: other
license_link: LICENSE
tags:

  • not-for-all-audiences

I wanted to improve on unalignment/toxic-dpo-v0.1 by having more natural-sounding responses and less numbered lists.
I used original prompts plus added around 40 unique new prompts related to medicine.

Issues:
there are some prompts that result in the model saying silly braindead things like adding up sugar blood level to blood pressure or going into thesaurus mode, will need fixes.

IDs of prompts are not unique, bear that in mind.

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.

  1. 2024-04-03Update README.md8c3cad3542 B
    Loading...
  2. 2024-04-02Update README.md55a310a357 B
    Loading...
  3. 2024-04-02Update README.md1c291b2327 B
    Loading...
  4. 2024-04-02Upload toxic_dpo_natural.jsoncfd6ce465 B
    Loading...
  5. 2024-04-02initial commiteacf79465 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.

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. 2024-04-03[bot] Conversion to Parquetclosed1 💬#1
    Loading...

Continue on Hugging Face →

Related datasets same stage · heal

argilla/distilabel-intel-orca-dpo-pairs
185.3K dl 185 likes 75.6 MB
distilabel Orca Pairs for DPO The dataset is a "distilabeled" version of the widely used dataset: Intel/orca_dpo_pairs. The ori...
arcee-ai/distilabel-intel-orca-dpo-pairs-binarized
141.3K dl 1 likes 29.5 MB
This is the binarized version of distilabel Orca Pairs for DPO and ORPO. Reference: https://huggingface.co/datasets/argilla/disti...
Intel/orca_dpo_pairs
124.5K dl 332 likes 34.6 MB
The dataset contains 12k examples from Orca style dataset Open-Orca/OpenOrca.
HuggingFaceH4/orca_dpo_pairs
73.3K dl 32 likes 29.4 MB
Dataset Card for Orca DPO Pair Dataset Description This is a pre-processed version of the OpenOrca dataset. The ...
argilla/dpo-mix-7k
60.9K dl 181 likes 23.1 MB
Argilla DPO Mix 7K Dataset A small cocktail combining DPO datasets built by Argilla with distilabel. The goal of this dataset ...
allenai/preference-test-sets
58K dl 29 likes 33.5 MB
Preference Test Sets Very few preference datasets have heldout test sets for validation of reward model accuracy results. In th...
llm-blender/Unified-Feedback
57.5K dl 18 likes 1.8 GB
Collections of pairwise feedback datasets. openai/summarize_from_feedback openai/webgpt_comparisons Dahoas/instruct-synthetic-pro...
mlabonne/orpo-dpo-mix-40k
50.1K dl 314 likes 120.6 MB
ORPO-DPO-mix-40k v1.2 This dataset is designed for ORPO or DPO training. See Fine-tune Llama 3 with ORPO for more information ...

Read further

Community best practices (healing)
4 rules on DPO/ORPO, GSM8K lag, CHES filtering, and what heal does not do.
M4 - Abliterate then heal
Two-stage pipeline. DPO healing recovers benchmarks.
The politics of dataset curation
Whose preferences are baked into the healing mix, and why it matters.
Non-English abliteration communities
The Russian slop-removal framing and non-English healing corpora.

Metadata

License
other

Repository

FILE .gitattributes FILE LICENSE FILE README.md FILE toxic_dpo_natural.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("adamo1139/toxic-dpo-natural-v1")
Raw snapshot (Python) 
from huggingface_hub import snapshot_download
snapshot_download(repo_id="adamo1139/toxic-dpo-natural-v1", repo_type="dataset")
git clone (requires git-lfs) 
git clone https://huggingface.co/datasets/adamo1139/toxic-dpo-natural-v1
Browse repository on Hugging Face ->
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.

Get the app Browse the catalog
Open in Abliteration