metaseq
YaLM-100B
metaseq | YaLM-100B | |
---|---|---|
53 | 35 | |
6,389 | 3,722 | |
0.4% | 0.1% | |
6.2 | 0.0 | |
11 days ago | 10 months ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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metaseq
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Training great LLMs from ground zero in the wilderness as a startup
This is a super important issue that affects the pace and breadth of iteration of AI almost as much as the raw hardware improvements do. The blog is fun but somewhat shallow and not technical or very surprising if you’ve worked with clusters of GPUs in any capacity over the years. (I liked the perspective of a former googler, but I’m not sure why past colleagues would recommend Jax over pytorch for LLMs outside of Google.) I hope this newco eventually releases a more technical report about their training adventures, like the PDF file here: https://github.com/facebookresearch/metaseq/tree/main/projec...
- Chronicles of Opt Development
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See the pitch memo that raised €105M for four-week-old startup Mistral
The number of people who can actually pre-train a true LLM is very small.
It remains a major feat with many tweaks and tricks. Case in point: the 114 pages of OPT175B logbook [1]
[1] https://github.com/facebookresearch/metaseq/blob/main/projec...
- Technologie: „Austro-ChatGPT“ – aber kein Geld zum Testen
- OPT (Open Pre-trained Transformers) is a family of NLP models trained on billions of tokens of text obtained from the internet
- Current state-of-the-art open source LLM
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Elon Musk Buys Ten Thousand GPUs for Secretive AI Project
Reliability at scale: take a look at the OPT training log book for their 175B model run. It needed a lot of babysitting. In my experience, that scale of TPU training run requires a restart about once every 1-2 weeks—and they provide the middleware to monitor the health of the cluster and pick up on hardware failures.
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Is AI Development more fun than Software Development?
I really appreciated this log of Facebook training a large language model of how troublesome AI development can be: https://github.com/facebookresearch/metaseq/tree/main/projects/OPT/chronicles
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Visual ChatGPT
Stable Diffusion will run on any decent gaming GPU or a modern MacBook, meanwhile LLMs comparable to GPT-3/ChatGPT have had pretty insane memory requirements - e.g., <https://github.com/facebookresearch/metaseq/issues/146>
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Ask HN: Is There On-Call in ML?
It seems so, check this log book from Meta: https://github.com/facebookresearch/metaseq/blob/main/projec...
YaLM-100B
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Elon Musk's Grok Exactly Echoes ChatGPT Responses: Identical Answers Raise Questions - EconoTimes
Its probably just open source software/training sets repurposed... https://github.com/yandex/YaLM-100B
- OpenAI CEO suggests international agency like UN's nuclear watchdog could oversee AI
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A few less Googleable questions about local LLMs
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
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Is it possible to use llama.cpp or create Alpaca Lora for YALM-100b model?
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
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Kandinsky 2.1 - a new open source text-to-Image model
Yandex has already released a LLM: https://github.com/yandex/YaLM-100B
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Just another casualty...
So there is this open project YaLM 100B require 200 GB of disk space, it is trained on 1.7 TB of text
- There's a lot of news about American/European AI. Do we know anything about what China, India, Russia and other countries are up to?
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Suggestion. Chat mode.
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...
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Ask HN: Can I download GPT / ChatGPT to my desktop?
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.
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[Rant] Siri is beyond horrendous and it’s even worse than ever
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.
What are some alternatives?
stable-diffusion - A latent text-to-image diffusion model
gpt-neox - An implementation of model parallel autoregressive transformers on GPUs, based on the DeepSpeed library.
nlp-resume-parser - NLP-powered, GPT-3 enabled Resume Parser from PDF to JSON.
SLIDE
GLM-130B - GLM-130B: An Open Bilingual Pre-Trained Model (ICLR 2023)
NeMo - A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)
gpt-2 - Code for the paper "Language Models are Unsupervised Multitask Learners"
mesh-transformer-jax - Model parallel transformers in JAX and Haiku
manim - Animation engine for explanatory math videos
YaLM-100B - Pretrained language model with 100B parameters
cupscale - Image Upscaling GUI based on ESRGAN
ClickHouse - ClickHouse® is a free analytics DBMS for big data