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unitaryai
detoxify
Python2020–2021
unitaryai / detoxify

detoxify

Trained models & code to predict toxic comments on all 3 Jigsaw Toxic Comment Challenges. Built using ⚡ Pytorch Lightning and 🤗 Transformers.

3Distinct people
3Mentions
0Explicit recommenders
1.3KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Trained models & code to predict toxic comments on all 3 Jigsaw Toxic Comment Challenges. Built using ⚡ Pytorch Lightning and 🤗 Transformers.

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month3 dated mentions

Observed mentions: 2020-11-12 10:15:17 UTC to 2021-11-10 21:15:47 UTC.

0122020-11-01 00:00:00 UTC to 2020-12-01 00:00:00 UTC (exclusive): 2 mentions; 2 submissions, 0 commentsNov 20202020-12-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-01-01 00:00:00 UTC to 2021-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-02-01 00:00:00 UTC to 2021-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-03-01 00:00:00 UTC to 2021-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-04-01 00:00:00 UTC to 2021-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-05-01 00:00:00 UTC to 2021-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsMay 20212021-06-01 00:00:00 UTC to 2021-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-07-01 00:00:00 UTC to 2021-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-08-01 00:00:00 UTC to 2021-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-09-01 00:00:00 UTC to 2021-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-10-01 00:00:00 UTC to 2021-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-11-01 00:00:00 UTC to 2021-12-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsNov 2021

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Nov 20202020-11-01 00:00:00 UTC2020-12-01 00:00:00 UTC220
Dec 20202020-12-01 00:00:00 UTC2021-01-01 00:00:00 UTC000
Jan 20212021-01-01 00:00:00 UTC2021-02-01 00:00:00 UTC000
Feb 20212021-02-01 00:00:00 UTC2021-03-01 00:00:00 UTC000
Mar 20212021-03-01 00:00:00 UTC2021-04-01 00:00:00 UTC000
Apr 20212021-04-01 00:00:00 UTC2021-05-01 00:00:00 UTC000
May 20212021-05-01 00:00:00 UTC2021-06-01 00:00:00 UTC000
Jun 20212021-06-01 00:00:00 UTC2021-07-01 00:00:00 UTC000
Jul 20212021-07-01 00:00:00 UTC2021-08-01 00:00:00 UTC000
Aug 20212021-08-01 00:00:00 UTC2021-09-01 00:00:00 UTC000
Sep 20212021-09-01 00:00:00 UTC2021-10-01 00:00:00 UTC000
Oct 20212021-10-01 00:00:00 UTC2021-11-01 00:00:00 UTC000
Nov 20212021-11-01 00:00:00 UTC2021-12-01 00:00:00 UTC101

What Hacker News says

3 sources
Yeah, this kind of toxic output sadly still can happen :-/ We have fully analyzed the training dataset (1128 GB) using Detoxify (https://github.com/unitaryai/detoxify) to filter out problematic content. But of course detecting toxicity is a tough challenge in itself, so this process is imperfect at best. We are using the RealToxicityPrompt framework (https://realtoxicityprompts.apps.allenai.org/) to analyse how toxic our models are and to steer our efforts in this direction. This means we are generating thousands of completions and analysing them to see how "nasty" the model is. We plan to write more on this topic soon. But yeah, this is definitely far from being a solved problem, and our model (as well as all large language models) should be handled with care.
In Show HN: Cedille, the largest French language model, released in open source

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