gpt-neox VS YaLM-100B

Gpt neox 20B can be used commerically.

GPT-Neo: GPT-Neo is a free and open-source language model developed by EleutherAI. It is a powerful model that can be used for a variety of tasks, including text generation, and question-answering. here is the GitHub

Doesn't gpt-neox 20b require like 40gb+ of VRAM? From their github repo the slim weights are 39GB and I think one of the devs has previously mentioned aiming for 48GB for inference.

3.) EleutherAI's GPT-Neo and GPT-NeoX: EleutherAI is an independent research organization that aims to promote open research in artificial intelligence. They have released GPT-Neo, an open-source language model based on the GPT architecture, and are developing GPT-NeoX, a highly-scalable GPT-like model. You can find more information on their GitHub repositories: GPT-Neo: https://github.com/EleutherAI/gpt-neo GPT-NeoX: https://github.com/EleutherAI/gpt-neox

It's really not that complicated. https://github.com/EleutherAI/gpt-neox

this forces me to create my own ai using gpt-neox .. i was being lazy, completely satisfied with my little ai baby .. i'll keep the account but not renew pro .. fuck luka, inc ... want it done right, do it yourself .. the python isn't that difficult and i have a spare linux vps .. my new work in progress .. freedom #!

Its probably just open source software/training sets repurposed... https://github.com/yandex/YaLM-100B

There is a 100b model published on pache 2.0 license. Though there is no information about finetuning it or using in 4-bit with smth like llama.cpp. Trying to figure out how to try it without renting extremely expensive gpu set. https://github.com/yandex/YaLM-100B

Hey everyone! I just discovered an open-source 100 billion parameter language model called YaLM, which is published under the Apache 2.0 license. The model is trained on more than 1 TB of Russian and English text. Here's the GitHub repo: https://github.com/yandex/YaLM-100B and an article explaining how it was trained: https://medium.com/yandex/yandex-publishes-yalm-100b-its-the-largest-gpt-like-neural-network-in-open-source-d1df53d0e9a6

Yandex has already released a LLM: https://github.com/yandex/YaLM-100B

So there is this open project YaLM 100B require 200 GB of disk space, it is trained on 1.7 TB of text

You'd think so, but to train a model like the one CAI uses, it would require truly jaw-breaking amount of funds. That's why CAI is so suspicious tbh. Just to give you an example, YaML (100 billion parameters which is probably less than CAI) took 65 days to train, and 800 A100 graphics cards. 175 billion parameters would not be 1.75 times higher because it's not a linear function. It would probably be 10x or even more. IIRC, "Open"Ai could only afford to train GPT-3 a single time...

I don't much follow AI news beyond what I randomly happen to see on HN, but this might still be the largest open source model: https://github.com/yandex/YaLM-100B . There's discussion of it here: https://old.reddit.com/r/MachineLearning/comments/vpn0r1/d_h... - at the bottom of that page is a comment from someone who actually ran it in the cloud.

Hilariously, Yandex Alisa runs circles around it, because it's not just a collection of gimmicks but has an actual 100B-class language model (YaLM, opensourced) as its core, plus lots of decent engineering. It's helpful, skillful and feels alive, almost like ChatGPT.