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> 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.

Showing 18 of 161 Qualified Libraries & Tools (Page 2 of 9)Accelerator Mappings & Failure Modes
Classical ML
3.46.0Apache-2.0

H2O

H2O.ai

Distributed in-memory machine learning and AutoML platform.

Training:
CPUCUDA
Inference:
CPU
#tabular
automl-hpo
1.1.1Apache-2.0

AutoGluon

Amazon Web Services (AWS)

AutoML for tabular, text, image, and time-series data with multi-layer ensembling.

Training:
CPUCUDA
Inference:
CPUCUDA
#tabular#text#image#multimodal
automl-hpo
2.3.2MIT

FLAML

Microsoft Research

A fast and lightweight library for automated machine learning and hyperparameter tuning.

Training:
CPUCUDA
Inference:
CPUCUDA
#tabular#text
NLP & LLM Serving
2.2.4Apache-2.0

Mamba (mamba-ssm)

Albert Gu & Tri Dao / State Spaces Team

Linear-time selective state space foundation architecture and CUDA kernels.

Training:
CUDA
Inference:
CUDA
#text#audio
Deep Learning
2.4.1BSD-3-Clause

PyTorch

Linux Foundation / PyTorch Foundation

Tensors and Dynamic neural networks in Python with strong GPU acceleration.

Training:
CPUCUDAROCMMPSXPUTPU
Inference:
CPUCUDAROCMMPS
#tabular#text#image#audio#multimodal
Deep Learning
2.17.0Apache-2.0

TensorFlow

Google

An end-to-end open source machine learning platform.

Training:
CPUCUDAROCMMPSTPU
Inference:
CPUCUDAROCMMPS
#tabular#text#image#audio
Deep Learning
3.5.0Apache-2.0

Keras

Keras Team / Google

Deep Learning for humans with multi-backend execution on PyTorch, JAX, and TensorFlow.

Training:
CPUCUDAROCMMPSTPU
Inference:
CPUCUDAROCMMPS
#image#text#tabular#multimodal
Deep Learning
0.4.35Apache-2.0

JAX

Google

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU.

Training:
CPUCUDAROCMTPU
Inference:
CPUCUDAROCM
#tabular#text#image#multimodal
Deep Learning
0.8.5Apache-2.0

Flax

Google Research

Flax: A neural network library and ecosystem for JAX designed for flexibility.

Training:
CPUCUDAROCMTPU
Inference:
CPUCUDAROCM
#text#image#multimodal
Deep Learning
3.0.0b1Apache-2.0

PaddlePaddle

Baidu

An easy-to-use, efficient, flexible and scalable industrial deep learning platform.

Training:
CPUCUDAROCMXPU
Inference:
CPUCUDAROCM
#image#text#multimodal
Deep Learning
2.3.1Apache-2.0

MindSpore

Huawei / OpenAtom Foundation

All-scenario deep learning framework tailored for Ascend AI processors.

Training:
CPUCUDA
Inference:
CPUCUDA
#text#image#multimodal
Deep Learning
0.15.1Apache-2.0

DeepSpeed

Microsoft

Deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Training:
CPUCUDAROCMXPU
Inference:
CPUCUDAROCM
#text#image#multimodal
Deep Learning
2.4.0Apache-2.0

PyTorch Lightning

Lightning AI

The deep learning framework to train, fine-tune and deploy AI models with PyTorch without the boilerplate.

Training:
CPUCUDAROCMMPSXPUTPU
Inference:
CPUCUDAROCMMPS
#image#text#audio#tabular#multimodal
Deep Learning
0.34.2Apache-2.0

Accelerate

Hugging Face

A simple library for training and using PyTorch models with multi-GPU, TPU, and mixed-precision.

Training:
CPUCUDAROCMMPSXPUTPU
Inference:
CPUCUDAROCMMPS
#text#image#audio#multimodal
NLP & LLM Serving
4.44.2Apache-2.0

Transformers

Hugging Face

State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

Training:
CPUCUDAROCMMPSXPUTPU
Inference:
CPUCUDAROCMMPS
#text#image#audio#multimodal
NLP & LLM Serving
3.1.1Apache-2.0

Sentence Transformers

Hugging Face / UKP Lab

Multilingual Sentence & Image Embeddings with BERT & Co.

Training:
CPUCUDAROCMMPSXPU
Inference:
CPUCUDAROCMMPS
#text#image#multimodal
NLP & LLM Serving
3.7.6MIT

spaCy

Explosion AI

Industrial-Strength Natural Language Processing in Python.

Training:
CPUCUDAMPS
Inference:
CPUCUDAMPS
#text
NLP & LLM Serving
3.9.1Apache-2.0

NLTK

NLTK Project

Natural Language Toolkit for Python education and linguistic analysis.

Training:
CPU
Inference:
CPU
#text