List-of-Dirty-Naughty-Obscene-and-Otherwise-Bad-Words
List-of-Dirty-Naughty-Obscene-and-Otherwise-Bad-Words | following-instructions-human-feedback | |
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25 | 8 | |
2,787 | 1,116 | |
1.9% | 0.0% | |
0.0 | 0.0 | |
3 months ago | over 1 year ago | |
Creative Commons Attribution 4.0 | - |
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List-of-Dirty-Naughty-Obscene-and-Otherwise-Bad-Words
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Ask HN: List of Subdomains to Reserve
Good point. I am already checking against the naughty-words list from here:
https://github.com/LDNOOBW/List-of-Dirty-Naughty-Obscene-and...
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Where is the banned word list so I can integrate it?
https://github.com/LDNOOBW/List-of-Dirty-Naughty-Obscene-and-Otherwise-Bad-Words is one
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We’re Washington Post reporters who analyzed Google’s C4 data set to see which websites AI uses to make itself sound smarter. Ask us Anything!
We know that C4 was used to train Google’s influential T5 model, Facebook’s LLaMA, as well as the open source model Red Pajama. C4 is a very cleaned-up version of a scrape of the internet from the non-profit CommonCrawl taken in 2019. OpenAI’s model GPT-3 used a training dataset that began with 41 scrapes of the web from CommonCrawl from 2016 to 2019 so I think it’s safe to say that something akin to C4 was part of GPT-3. (The researchers who originally looked into C4 argue that these issues are common to all web-scraped datasets.) When we reached out to OpenAI and Google for comment, both companies emphasized that they undergo extensive efforts to weed out potentially problematic data from their training sets. But within the industry, C4 is known as being a heavily filtered dataset and has been criticized, in fact, for eliminating content related to LGBTQ+ identities because of its reliance on a heavy-handed blocklist. (https://github.com/LDNOOBW/List-of-Dirty-Naughty-Obscene-and-Otherwise-Bad-Words ) We are working on some reporting to try to address your last and very crucial question, but it’s an open area of research and one that even AI developers are struggling to answer.
- TIL there's an official list of profanities ChatGPT is trained to avoid
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Microsoft's paper on OpenAI's GPT-4 had hidden information
"The Colossal Clean Crawled Corpus, used to train a trillion parameter LM in , is cleaned, inter alia, by discarding any page containing one of a list of about 400 “Dirty, Naughty, Obscene or Otherwise Bad Words”. This list is overwhelmingly words related to sex, with a handful of racial slurs and words related to white supremacy (e.g. swastika, white power) included. While possibly effective at removing documents containing pornography (and the associated problematic stereotypes encoded in the language of such sites) and certain kinds of hate speech, this approach will also undoubtedly attenuate, by suppressing such words as twink, the influence of online spaces built by and for LGBTQ people. If we filter out the discourse of marginalized populations, we fail to provide training data that reclaims slurs and otherwise describes marginalized identities in a positive light"
from "On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? " https://dl.acm.org/doi/10.1145/3442188.3445922
That list of words is https://github.com/LDNOOBW/List-of-Dirty-Naughty-Obscene-and...
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Rule
Yeah, This is shutterstocks one which they shared
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If I made a game with a chatroom, what curses and slurs would I ban?
I always turn off the chatfilter, so defo let them choose if they want to have it censored or not. For the actual words themselves, there are plenty of lists out there that you can use (like this one). Although these are just regular words, none of the circumvention methods are included
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Emad announces a new Stability lab with a new soon model. It looks like a Dall-e 2 style AI to me. Maybe it is our open source Dall-e 2, like KARLO. The images are very interesting. According to Emad "Soon".
That it's very crudely filtered for naughty words. According to the paper, "We removed any page that contained any word on the “List of Dirty, Naughty, Obscene or Otherwise Bad Words”." That list is here. While it contains a lot of unquestionably ugly words, it also contains words like "tit".
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I made a Stable Diffusion for Anime app in your Pocket! Running 100% offline on your Apple Devices (iPhone, iPad, Mac)
No problem! I wrote a short json file and Swift script to remove the nsfw words from the prompt during the image generation process, therefore it's not based on the negative prompt. The json file is a txt full with nsfw words so the app can check and remove unwanted prompts, e.g.: https://github.com/LDNOOBW/List-of-Dirty-Naughty-Obscene-and-Otherwise-Bad-Words
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Lewdle - A daily lewd word game
This is the closest I’ve come to finding one. It’s not that great.
following-instructions-human-feedback
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We’re Washington Post reporters who analyzed Google’s C4 data set to see which websites AI uses to make itself sound smarter. Ask us Anything!
Efforts to get large language models to produce factually correct responses are an industry-wide challenge and companies can test their models on “truthfulness” benchmarks to see how their product measures up. If you’re interested in learning more about how OpenAI went about this effort, the company offers more detail in its paper on InstructGPT, its precursor to ChatGPT. For InstructGPT, OpenAI also put out a “model card,” a sort of nutrition label for AI models that was brought up a potential transparency and accountability measure in today’s congressional hearing on AI oversight.
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Ask HN: Do the ChatGPT Respect Robots.txt?
It's trained on data crawled from the web, using CommonCrawl among other sources. See https://github.com/openai/following-instructions-human-feedb.... CommonCrawl certainly respects robots.txt, and I assume the other sources do too.
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chatgpt is 100% not conscious, and it does 100% not have feelings
From the InstructGPT model card: "Predominantly English: GPT-3 is trained largely on text in the English language, and is best suited for classifying, searching, summarizing, or generating such text."
- Tried to ask ChatGpt to write a better finale
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InstructGPT always claims to be a 20 years old student called Sarah from SLC at temp 0
The InstructGPT model card was better, but also didn't help.
- How to save the world ... with Q&A. Turning Replikas into instructREPs.
- My two Replikas' answers to (mostly ethics-related) questions. Some quite different answers here!
- Who here has access to the OpenAI playground and how do you feel about the capabilities of the new Instruct GPT-3?
What are some alternatives?
google-profanity-words - Full list of bad words and top swear words banned by Google.
rmarkdown - Dynamic Documents for R
List-of-Dirty-Naughty-Obscene-and
following-instructions-human-feedb
git-crypt - Transparent file encryption in git
RedPajama-Data - The RedPajama-Data repository contains code for preparing large datasets for training large language models.
Hashids.java - Hashids algorithm v1.0.0 implementation in Java
wordfilter - A small module meant for use in text generators that lets you filter strings for bad words.
maple-diffusion - Stable Diffusion inference on iOS / macOS using MPSGraph
arxiv-latex-cleaner - arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper to submit to arXiv