grok-1
trax
grok-1 | trax | |
---|---|---|
8 | 7 | |
48,188 | 7,960 | |
4.5% | 0.4% | |
5.9 | 4.7 | |
7 days ago | 3 months ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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grok-1
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Maxtext: A simple, performant and scalable Jax LLM
Is t5x an encoder/decoder architecture?
Some more general options.
The Flax ecosystem
https://github.com/google/flax?tab=readme-ov-file
or dm-haiku
https://github.com/google-deepmind/dm-haiku
were some of the best developed communities in the Jax AI field
Perhaps the “trax” repo? https://github.com/google/trax
Some HF examples https://github.com/huggingface/transformers/tree/main/exampl...
Sadly it seems much of the work is proprietary these days, but one example could be Grok-1, if you customize the details. https://github.com/xai-org/grok-1/blob/main/run.py
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Elon Musk's xAI previews Grok-1.5V, its first multimodal model
Anyone know the system requirements? Anyone even able to run it? In their last release "grok 1" the issues are full of people who can't even run it: https://github.com/xai-org/grok-1/issues
- Grok-1 Weights Published
- Grok-1
- FLaNK AI Weekly 18 March 2024
- X.ai's Grok-1 Model Is Officially Open-Source and Larger Than Expected
- Grok-1 (LLM with 314B parameters) is now source
- Elon drops open source Grok onto the stage
trax
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Maxtext: A simple, performant and scalable Jax LLM
Is t5x an encoder/decoder architecture?
Some more general options.
The Flax ecosystem
https://github.com/google/flax?tab=readme-ov-file
or dm-haiku
https://github.com/google-deepmind/dm-haiku
were some of the best developed communities in the Jax AI field
Perhaps the “trax” repo? https://github.com/google/trax
Some HF examples https://github.com/huggingface/transformers/tree/main/exampl...
Sadly it seems much of the work is proprietary these days, but one example could be Grok-1, if you customize the details. https://github.com/xai-org/grok-1/blob/main/run.py
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Replit's new Code LLM was trained in 1 week
and the implementation https://github.com/google/trax/blob/master/trax/models/resea... if you are interested.
Hope you get to look into this!
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RedPajama: Reproduction of Llama with Friendly License
Thank you for developing the pipeline and amassing considerable compute for gathering and preprocessing this dataset!
I'm not sure if this is the right place to ask about this, but could you consider training an LLM using a more advanced, sparse transformer architecture (specifically, "Terraformer" from this paper https://arxiv.org/abs/2111.12763 and this codebase https://github.com/google/trax/blob/master/trax/models/resea... by Google Brain and OpenAI)? I understand the pressure to focus on training a straightforward LLaMA replication, but of course you see that it's a legacy dense architecture which limits its inference performance. This new architecture is not just an academic curiosity but is already validated at scale by Google, providing 10x+ inference performance boost on the same hardware.
Frankly, the community's compute budget - for training and for inference - isn't infinite, and neither is the public's interest in models that do not have advantage (at least in convenience) over closed-source ones; and so we should utilize both those resources as efficiently as possible. It could be a big step forward if you trained at least LLaMA-Terraformer-7B and 13B foundation models on the whole dataset.
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The founder of Gmail claims that ChatGPT can “kill” Google in two years.
But a couple years later they came out with open source implementations yeah: https://github.com/google/trax/tree/master/trax/models/reformer
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[D] Paper Explained - Sparse is Enough in Scaling Transformers (aka Terraformer) | Video Walkthrough
Code: https://github.com/google/trax/blob/master/trax/examples/Terraformer_from_scratch.ipynb
- Why would I want to develop yet another deep learning framework?
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How to train large models on a normal laptop?
Training language models is expensive. Train the biggest model you can afford. I assume you've tried the colab from the reformer GitHub: https://github.com/google/trax/tree/master/trax/models/reformer
What are some alternatives?
FLaNK-python-processors - Many processors
flax - Flax is a neural network library for JAX that is designed for flexibility.
rnote - Sketch and take handwritten notes.
dm-haiku - JAX-based neural network library
pytorch-image-models - PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNet-V3/V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
muzero-general - MuZero
sqlglot - Python SQL Parser and Transpiler
ML-Optimizers-JAX - Toy implementations of some popular ML optimizers using Python/JAX
quarto-cli - Open-source scientific and technical publishing system built on Pandoc.
extending-jax - Extending JAX with custom C++ and CUDA code
openvino_notebooks - 📚 Jupyter notebook tutorials for OpenVINO™
objax