mesh-transformer-jax
YaLM-100B
mesh-transformer-jax | YaLM-100B | |
---|---|---|
52 | 35 | |
6,213 | 3,722 | |
- | 0.1% | |
0.0 | 0.0 | |
over 1 year ago | 10 months ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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mesh-transformer-jax
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Large Language Models: Compairing Gen2/Gen3 Models (GPT-3, GPT-J, MT5 and More)
GPT-J is a LLM case study with two goals: Training a LLM with a data source containing unique material, and using the training frameworkMesh Transformer JAX to achieve a high training efficiency through parallelization. There is no research paper about GPT-J, but on its GitHub pages, the model, different checkpoints, and the complete source code for training is given.
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[R] Parallel Attention and Feed-Forward Net Design for Pre-training and Inference on Transformers
This idea has already been proposed in ViT-22B and GPT-J-6B.
- Show HN: Finetune LLaMA-7B on commodity GPUs using your own text
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[D] An Instruct Version Of GPT-J Using Stanford Alpaca's Dataset
Sure. Here's the repo I used for the fine-tuning: https://github.com/kingoflolz/mesh-transformer-jax. I used 5 epochs, and appart from that I kept the default parameters in the repo.
- Boss wants me to use ChatGPT for work, but I refuse to input my personal phone number. Any advice?
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Let's build GPT: from scratch, in code, spelled out by Andrej Karpathy
You can skip to step 4 using something like GPT-J as far as I understand: https://github.com/kingoflolz/mesh-transformer-jax#links
The pretrained model is already available.
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Best coding model?
The Github repo suggests it's possible you can change the number of checkpoints to make it run on a GPU.
- Ask HN: What language models can I fine-tune at home?
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selfhosted/ open-source ChatGPT alternative?
GPT-J, which uses mesh-transformer-jax: https://github.com/kingoflolz/mesh-transformer-jax
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GPT-J, an open-source alternative to GPT-3
They hinted at it in the screenshot, but the goods are linked from the https://6b.eleuther.ai page: https://github.com/kingoflolz/mesh-transformer-jax#gpt-j-6b (Apache 2)
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?
DeepSpeed - DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
gpt-neox - An implementation of model parallel autoregressive transformers on GPUs, based on the DeepSpeed library.
tensorflow - An Open Source Machine Learning Framework for Everyone
SLIDE
gpt-neo - An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.
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)
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
YaLM-100B - Pretrained language model with 100B parameters
KoboldAI-Client
ClickHouse - ClickHouse® is a free analytics DBMS for big data
alpaca-lora - Instruct-tune LLaMA on consumer hardware
metaseq - Repo for external large-scale work