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EleutherAI
gpt-neo
Python2021–2026
EleutherAI / gpt-neo · Archived

gpt-neo

An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.

AI & Machine LearningLibraries & SDKs
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11Distinct people
11Mentions
0Explicit recommenders
8.2KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

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

Also in these discussions

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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 year11 dated mentions

Observed mentions: 2021-01-01 23:15:12 UTC to 2026-08-10 20:20:55 UTC.

02468102021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 9 mentions; 1 submissions, 8 comments20212022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20232024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-01-01 00:00:00 UTC to 2027-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments. Incomplete calendar period.2026*

* An incomplete calendar period is marked with an outlined bar. Its count is not directly comparable with a full period.

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
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC918
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC101
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC000
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC000
2026 (partial)2026-01-01 00:00:00 UTC2027-01-01 00:00:00 UTC101

What Hacker News says

11 sources
canyon289·Aug 10, 2026
Disclaimer, I work on Gemma and open models at Deepmind and the opinions here are my own There were open models from EleutherAI (GPT-Neo), Google Brain (T5X, Bert), and HuggingFace was promoting open models (and others doing open work I haven't listed here) all prior to 2023 and the big Chatgpt moment. https://github.com/EleutherAI/gpt-neo/releases https://github.com/google-research/bert https://github.com/google-research/t5x If you're learning about AI models it's still worthwhile to review these models and codebases because they continue to be the basis of the technology that's being produced today! It'll give you a good perspective of how things have changed, similar to say learning about propeller planes before moving onto modern jet engines.
In Mark Zuckerberg attacks 'closed' AI rivals as Meta returns to open models
sillysaurusx·Jul 4, 2021
just happy I won a big blue gorilla at a carnival. https://twitter.com/theshawwn/status/1411519063432519680 Plus it's looking more and more like I'll be getting a job in finance with a fat salary. First interview's on monday. Tonight I felt "This is it -- if getting a few dozen people to sign up for TFRC is the only way I can make an impact, then at least I'll be ending my ML streak on a high note." It's truly amazing to me that the world hasn't noticed how incredible TFRC is. It's literally the reason Eleuther exists at all. If that sounds ridiculous, remember that there was a time when Connor's TPU quota was the only reason everyone was able to band together and start building GPT neo. https://github.com/EleutherAI/gpt-neo At least I was able to start a discord server that happened to get the original eleuther people together in the rig
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ht place at the right time to decide to do any of that. But the root of all of it is TFRC. Always has been. Without them, I would've given up ML long ago. Because trying to train anything on GPUs with Colab is just ... so frustrating. I would have fooled around a bit with ML, but I wouldn't have decided to pour two years of my life into mastering it. Why waste your time? Five years from now, Jax + TPU VMs are going to wipe pytorch off the map. So I'll be making bank at a finance company, eating popcorn like "told ya so" and looking back wistfully at days like today. Everyone in ML is so cool. Was easily the best two years of my life as a developer. I know all this is kind of weird to pour out, but I don't care -- everyone here owes everything to the geniuses that bequeathed TFRC unto the world. For now, I slink back into the shadows, training tentacle porn GANs in secret, emerging only once in a blue moon to shock the world with weird ML things. Muahaha. </ml>
In GPT-J-6B – A 6 billion parameter, autoregressive text generation model
minimaxir·Mar 29, 2021
As someone who works on a Python library solely devoted to making AI text generation more accessible to the normal person (https://github.com/minimaxir/aitextgen ) I think the headline is misleading. Although the article focuses on the release of GPT-Neo, even GPT-2 released in 2019 was good at generating text, it just spat out a lot of garbage requiring curation, which GPT-3/GPT-Neo still requires albeit with a better signal-to-noise ratio. Most GPT-3 demos on social media are survivorship bias. (in fact OpenAI's rules for the GPT-3 API strongly encourage curating such output) GPT-Neo, meanwhile, is such a big model that it requires a bit of data engineering work to get operating and generating text (see the README: https://github.com/EleutherAI/gpt-neo ), and it's unclear currently if it's as good as GPT-3, even when comparing models ap
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ples-to-apples (i.e. the 2.7B GPT-Neo with the "ada" GPT-3 via OpenAI's API). That said, Hugging Face is adding support for GPT-Neo to Transformers (https://github.com/huggingface/transformers/pull/10848 ) which will help make playing with the model easier, and I'll add support to aitextgen if it pans out.
In The makers of Eleuther hope it will be an open source alternative to GPT-3
PufPufPuf·Mar 24, 2021
I tried the same prompt on the open-source recreation of OpenAI GPT-3 -- GPT Neo (https://github.com/EleutherAI/gpt-neo), specifically on their 2.7B model -- which should correspond to the smallest model in the article (Ada) that produced just pure garbage. The result is surprisingly good: 1. How did this little blossom happen? When are you going to bloom? 2. Have you ever thought about a dark horse in the running for Miss November? 3. You can spot the man who loves me by my neck – and he definitely knows it. 4. Are there any lucky cats who get to sleep in my bed every night? 5. Are black and whites everywhere? Running for the hills 6. My younger brother and I used to play a game. He’d pretend to be a bull in the pasture, and I’d pretend to be the one being held. 7. Why was this movie rated PG? Because it’s rated PG. 8. When is the last t
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ime you had to see a movie in children’s theaters? 9. You are so sexy I would hate for anyone to see you down here 10. I’d love to sleep with you right now, but I have a child with me
In GPT-3 tries pickup lines

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