Topics / #jax

Jax projects on GitHub

The JAX library for high-performance numerical computing and machine learning research.

As of , the most-starred Jax projects on GitHub are transformers (167.8K stars), keras (64.4K stars) and grok-1 (52.2K stars). GitHub.Locker tracks 23 Jax repositories with 597.3K stars combined. The fastest-growing on October 18 was transformers, with +42 stars in a day.

23Projects
597.3KStars in total
+126Stars in a day
Browse in the catalog →github.com/topics/jax ↗

Hot right now

Most stars gained in a day · Oct 18

+42

transformers

huggingface/transformers · ★ 167.8K

Transformers is Hugging Face's model-definition framework for state-of-the-art machine learning models across text, vision, audio, video, and multimodal tasks, usable for both inference and training.

+15

needle

cactus-compute/needle · ★ 14.1K

Needle 2 is an open 45M-parameter model for tool calling, device use and structured extraction that ships as a single 14MB binary and runs a full session in about 28MB of RAM. This repo is its Python package for inference, LoRA fine-tuning and export.

+14

openpi

Physical-Intelligence/openpi · ★ 14.3K

openpi is a collection of open-source vision-language-action (VLA) models for robotics from the Physical Intelligence team, including pi0, pi0-FAST, and pi0.5, with pretrained checkpoints and code for fine-tuning and running them.

+14

kaggle-tpu-lab

ARahim3/kaggle-tpu-lab · ★ 683

A recipe that serves frontier-class open LLMs — GLM-5.3-Flash 320B MoE and Qwen3.8-27B bf16 — on Kaggle's free TPU v5e-8, exposing a public OpenAI-compatible (and Anthropic-compatible) endpoint you can plug into coding agents like Claude Code, Codex, opencode, or pi.

The all-time top

23 projects · by stars

  1. #1 · huggingface/transformers

    transformers

    Transformers is Hugging Face's model-definition framework for state-of-the-art machine learning models across text, vision, audio, video, and multimodal tasks, usable for both inference and training.

    167.8K
  2. #2 · keras-team/keras

    keras

    Keras 3 is a multi-backend deep learning framework that lets you build and train models for computer vision, NLP, audio, timeseries, and recommender systems on top of JAX, TensorFlow, or PyTorch.

    64.4K
  3. #3 · xai-org/grok-1

    grok-1

    Grok-1 is the 314B-parameter Mixture-of-Experts language model that xAI opened up; this repository holds the JAX example code for loading and running it.

    52.2K
  1. 4

    LLM101n

    37.5Kkarpathy/LLM101n

    LLM101n is a planned course by Andrej Karpathy that walks through building a 'Storyteller' AI language model end-to-end, from basics all the way to a ChatGPT-like web app, implemented from scratch in Python, C and CUDA.

  2. 5

    jax

    36.5Kjax-ml/jax · Python

    JAX is a Python library for accelerator-oriented array computation and program transformation, built for high-performance numerical computing and large-scale machine learning.

  3. 6

    d2l-en

    29.9Kd2l-ai/d2l-en · Python

    An interactive open-source deep learning book that teaches concepts, context, and runnable code together, with examples in multiple frameworks. Its premise: the best way to understand deep learning is learning by doing.

  4. 7

    best-of-ml-python

    23.8Klukasmasuch/best-of-ml-python

    A curated, ranked index of top open-source machine learning libraries for Python, covering areas like deep learning, NLP, AutoML and data visualization, generated and refreshed automatically.

  5. 8

    datasets

    22.1Khuggingface/datasets · Python

    A lightweight Python library from Hugging Face that gives one-line dataloaders for a huge catalog of ready-to-use public datasets on the HF Hub, plus fast, reproducible preprocessing for Hub and local data.

  6. 9

    deep-learning-with-python-notebooks

    20.3Kfchollet/deep-learning-with-python-notebooks · Jupyter Notebook

    Companion Jupyter notebooks for the book 'Deep Learning with Python' by Francois Chollet (and Matthew Watson for the 3rd edition, 2025), implementing all its code samples, plus legacy notebooks for the 2nd edition (2021) and 1st edition (2017).

  7. 10

    transformers.js

    16.4Khuggingface/transformers.js · JavaScript

    Transformers.js lets you run Hugging Face's state-of-the-art machine learning models directly in a web browser, with no server required, using an API designed to mirror the Python transformers library.

  8. 11

    OpenMythos

    14.9Kkyegomez/OpenMythos · Python

    OpenMythos is an open-source, speculative PyTorch implementation that tries to reconstruct the internal architecture of Anthropic's Claude ('Mythos') purely from publicly available research papers, not from any leaked or official Anthropic code.

  9. 12

    dalle-mini

    14.7Kborisdayma/dalle-mini · Python

    DALL·E Mini is an open-source model that generates images from a text prompt, built as a smaller, reproducible version of OpenAI's DALL·E.

  10. 13

    openpi

    14.3KPhysical-Intelligence/openpi · Python

    openpi is a collection of open-source vision-language-action (VLA) models for robotics from the Physical Intelligence team, including pi0, pi0-FAST, and pi0.5, with pretrained checkpoints and code for fine-tuning and running them.

  11. 14

    ivy

    14.2Kunifyai/ivy · Python

    Ivy is an open-source Python library that converts machine learning code between frameworks — you can transpile ML models, tools and libraries from one framework to another with ivy.transpile.

  12. 15

    needle

    14.1Kcactus-compute/needle · Python

    Needle 2 is an open 45M-parameter model for tool calling, device use and structured extraction that ships as a single 14MB binary and runs a full session in about 28MB of RAM. This repo is its Python package for inference, LoRA fine-tuning and export.

  13. 16

    vision_transformer

    12.7Kgoogle-research/vision_transformer · Jupyter Notebook

    This is Google Research's official JAX/Flax code release for Vision Transformer (ViT) and MLP-Mixer image classification models, including pretrained checkpoints and scripts to fine-tune them on your own data.

  14. 17

    wandb

    11.3Kwandb/wandb · Python

    wandb is the Weights & Biases AI developer platform: a Python library and hosted service for tracking, visualizing, and managing machine learning experiments from datasets to production models, including LLM apps via its Weave toolset.

  15. 18

    dopamine

    10.9Kgoogle/dopamine · Jupyter Notebook

    Dopamine is a research framework for fast prototyping of reinforcement learning algorithms — a deliberately small, easily grokked codebase meant for trying out speculative research ideas.

  16. 19

    cleanrl

    10.6Kvwxyzjn/cleanrl · Python

    CleanRL is a collection of high-quality single-file implementations of deep reinforcement learning algorithms (PPO, DQN, C51, SAC, DDPG, TD3, PPG and more), written to be read and tweaked rather than imported.

  17. 20

    maths-cs-ai-compendium

    7.7KHenryNdubuaku/maths-cs-ai-compendium · TypeScript

    An open, unconventional online textbook covering maths, computing and AI from the ground up — intuition first, real-world context, for practitioners who want deep understanding rather than exam survival.

  18. 21

    kaggle-tpu-lab

    683ARahim3/kaggle-tpu-lab · Python

    A recipe that serves frontier-class open LLMs — GLM-5.3-Flash 320B MoE and Qwen3.8-27B bf16 — on Kaggle's free TPU v5e-8, exposing a public OpenAI-compatible (and Anthropic-compatible) endpoint you can plug into coding agents like Claude Code, Codex, opencode, or pi.

  19. 22

    StreamPI

    211hku-sail/StreamPI · Python

    Official code of StreamPI (NeurIPS 2026, from HKU and ACE Robotics): a streaming temporal modeling framework that gives VLA robot policies like pi0.5 memory of past frames and multi-frame perception without adding any new parameters.

  20. 23

    tpu-megakernels

    163Inferact/tpu-megakernels · Python

    A companion research repo with fused 'megakernel' decode implementations for two models on Google TPUs: Kimi K3 with DSpark speculative decoding, and Qwen3.8-27B with DFlash2 speculative decoding, written to accompany the blog post '700 TPS on Kimi K3: A Case for TPU Megakernels'.

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