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Top 23 Jax Open-Source Projects
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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jax
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
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d2l-en
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
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wandb
🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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einops
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
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interviews.ai
It is my belief that you, the postgraduate students and job-seekers for whom the book is primarily meant will benefit from reading it; however, it is my hope that even the most experienced researchers will find it fascinating as well.
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foolbox
A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX
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EasyLM
Large language models (LLMs) made easy, EasyLM is a one stop solution for pre-training, finetuning, evaluating and serving LLMs in JAX/Flax.
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Project mention: Maxtext: A simple, performant and scalable Jax LLM | news.ycombinator.com | 2024-04-23Is 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
As a beginner, I was looking for something simple and flexible for developing deep learning models and that is when I found Keras. Many AI/ML professionals appreciate Keras for its simplicity and efficiency in prototyping and developing deep learning models, making it a preferred choice, especially for beginners and for projects requiring rapid development.
The dual numbers exist just as surely as the real numbers and have been used well over 100 years
https://en.m.wikipedia.org/wiki/Dual_number
Pytorch has had them for many years.
https://pytorch.org/docs/stable/generated/torch.autograd.for...
JAX implements them and uses them exactly as stated in this thread.
https://github.com/google/jax/discussions/10157#discussionco...
As you so eloquently stated, "you shouldn't be proclaiming things you don't actually know on a public forum," and doubly so when your claimed "corrections" are so demonstrably and totally incorrect.
See also https://github.com/unifyai/ivy which I have not tried but seems along the lines of what you are describing, working with all the major frameworks
Project mention: A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev | dev.to | 2024-02-05Weights & Biases — The developer-first MLOps platform. Build better models faster with experiment tracking, dataset versioning, and model management. Free tier for personal projects only, with 100 GB of storage included.
Project mention: Maxtext: A simple, performant and scalable Jax LLM | news.ycombinator.com | 2024-04-23Is 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
Project mention: Einops: Flexible and powerful tensor operations for readable and reliable code | news.ycombinator.com | 2023-12-12
Project mention: Maxtext: A simple, performant and scalable Jax LLM | news.ycombinator.com | 2024-04-23Is 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
Project mention: Maxtext: A simple, performant and scalable Jax LLM | news.ycombinator.com | 2024-04-23Is 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
Project mention: JAX – NumPy on the CPU, GPU, and TPU, with great automatic differentiation | news.ycombinator.com | 2023-09-28Agree, though I wouldn’t call PyTorch a drop-in for NumPy either. CuPy is the drop-in. Excepting some corner cases, you can use the same code for both. Thinc’s ops work with both NumPy and CuPy:
https://github.com/explosion/thinc/blob/master/thinc/backend...
Go ahead, play with any adversarial attacks from https://github.com/bethgelab/foolbox you will not find an attack that is both robust to perturbations and almost visually imperceptible
Glicol looks very cool! Also check out Faust if you haven't (https://faust.grame.fr), another FP sound programming language.
Project mention: Calyx, a Compiler Infrastructure for Accelerator Generators | news.ycombinator.com | 2024-03-04How is this different than the mlir infrastructure of llvm and xla implemented in https://iree.dev/?
Project mention: Maxtext: A simple, performant and scalable Jax LLM | news.ycombinator.com | 2024-04-23
is used to capture the power of a fully-trained deep net of infinite width.
https://openreview.net/pdf?id=rkl4aESeUH, https://github.com/google/neural-tangents
> It has long been known that a single-layer fully-connected neural network with an i.i.d. prior over its parameters is equivalent to a Gaussian process (GP), in the limit of infinite network width.
https://arxiv.org/abs/1711.00165
And of course, one needs to look back at SVMs applying a kernel function and separating with a line, which looks a lot like an ANN with a single hidden layer followed by a linear mapping.
https://stats.stackexchange.com/questions/238635/kernel-meth...
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
Jax related posts
- Maxtext: A simple, performant and scalable Jax LLM
- The Elements of Differentiable Programming
- Gemma.cpp: lightweight, standalone C++ inference engine for Gemma models
- Bayesian Analysis with Python
- Julia GPU-based ODE solver 20x-100x faster than those in Jax and PyTorch
- Show HN: WebGPU Particles Simulation
- [P] LagrangeBench: A Lagrangian Fluid Mechanics Benchmarking Suite
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www.saashub.com | 26 Apr 2024
Index
What are some of the best open-source Jax projects? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | transformers | 125,021 |
| 2 | Keras | 60,937 |
| 3 | jax | 27,936 |
| 4 | d2l-en | 21,628 |
| 5 | best-of-ml-python | 15,302 |
| 6 | ivy | 14,022 |
| 7 | wandb | 8,190 |
| 8 | trax | 7,953 |
| 9 | einops | 7,916 |
| 10 | pyprobml | 6,243 |
| 11 | flax | 5,497 |
| 12 | interviews.ai | 4,437 |
| 13 | datasets | 4,162 |
| 14 | scenic | 2,995 |
| 15 | alpa | 2,983 |
| 16 | dm-haiku | 2,806 |
| 17 | thinc | 2,789 |
| 18 | foolbox | 2,655 |
| 19 | faust | 2,408 |
| 20 | iree | 2,379 |
| 21 | deepxde | 2,328 |
| 22 | EasyLM | 2,228 |
| 23 | neural-tangents | 2,219 |
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