> ML_LIBRARIES_CATALOG_v1.0
Qualified ML Libraries
Every library is independently qualified with primary citations, supported version ranges, hardware accelerator separation, and real-world failure patterns.
H2O
H2O.ai
Distributed in-memory machine learning and AutoML platform.
AutoGluon
Amazon Web Services (AWS)
AutoML for tabular, text, image, and time-series data with multi-layer ensembling.
FLAML
Microsoft Research
A fast and lightweight library for automated machine learning and hyperparameter tuning.
Mamba (mamba-ssm)
Albert Gu & Tri Dao / State Spaces Team
Linear-time selective state space foundation architecture and CUDA kernels.
PyTorch
Linux Foundation / PyTorch Foundation
Tensors and Dynamic neural networks in Python with strong GPU acceleration.
TensorFlow
An end-to-end open source machine learning platform.
Keras
Keras Team / Google
Deep Learning for humans with multi-backend execution on PyTorch, JAX, and TensorFlow.
JAX
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU.
Flax
Google Research
Flax: A neural network library and ecosystem for JAX designed for flexibility.
PaddlePaddle
Baidu
An easy-to-use, efficient, flexible and scalable industrial deep learning platform.
MindSpore
Huawei / OpenAtom Foundation
All-scenario deep learning framework tailored for Ascend AI processors.
DeepSpeed
Microsoft
Deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
PyTorch Lightning
Lightning AI
The deep learning framework to train, fine-tune and deploy AI models with PyTorch without the boilerplate.
Accelerate
Hugging Face
A simple library for training and using PyTorch models with multi-GPU, TPU, and mixed-precision.
Transformers
Hugging Face
State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Sentence Transformers
Hugging Face / UKP Lab
Multilingual Sentence & Image Embeddings with BERT & Co.
spaCy
Explosion AI
Industrial-Strength Natural Language Processing in Python.
