# apple/axlearn

An Extensible Deep Learning Library

Repository: https://github.com/apple/axlearn
Canonical: https://ross.abutalabs.com/products/axlearn
Language: Python
License: Apache-2.0
License Family: permissive
Topics: deep-learning, jax
Last push: 2026-07-08T21:26:38+00:00

## Health v2 (maintenance only)
Score: 71/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 91, release rhythm 35, longevity 91
- inputs: {"age_days": 1286, "days_push": 56, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2372, forks 406 (observed 2026-08-28T04:06:41.859669+00:00)

## What it is
AXLearn is a Python deep learning library built on JAX and XLA for developing and training large-scale models, with an object-oriented configuration system for composing reusable model components. It scales to hundreds of billions of parameters across thousands of accelerators and supports NLP, vision, and speech workloads on public clouds.

## Use cases
- train large language models on thousands of accelerators
- build deep learning models with a composable configuration system
- run large-scale training jobs on public clouds
- train speech recognition or computer vision models at scale
- integrate Flax or Hugging Face transformers models into a JAX training pipeline
- manage and deploy distributed training jobs and data

## When to choose
- you need to train models with tens or hundreds of billions of parameters
- you want JAX/XLA-based training with high accelerator utilization
- you need cloud tooling for deploying and managing large training jobs
- you prefer an object-oriented, modular approach to model composition

## When to avoid
- you need a stable API, since it is under active development and subject to change
- you want a lightweight library for small models or quick experiments
- you prefer PyTorch or TensorFlow ecosystems
- you lack access to large accelerator clusters

## Facets
- artifact type: library
- maturity: active
- function: deep-learning, llm-training, machine-learning, cli
- domain: deep-learning, machine-learning, large-language-models, computer-vision, speech-processing, gpu-computing
- platform: python, cloud
- tags: jax, xla, gspmd, large-scale-training, distributed-training, model-training, flax, huggingface, natural-language-processing, gpu, linux

## Member repositories
- apple/axlearn (main) score 71

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:41.859669+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:35:09.026887+00:00, confidence not recorded.
  - readme: https://github.com/apple/axlearn (fetched 2026-08-28T04:06:41.859669+00:00, sha 98a0349e3197)
- Data as of 2026-08-30T08:39:29.467469+00:00.