Framework Guides

Here is the list of supported ML libraries and formats in BentoML. You can also find example projects in the bentoml/examples directory.

CatBoost

fast.ai

Keras

LightGBM

MLflow

ONNX

PyTorch

PyTorch Lightning

Scikit-Learn

TensorFlow

Transformers

XGBoost

Detectron2

EasyOCR

Custom Models

Picklable Model

Custom Runner

Roadmap

The following frameworks are supported in pre-1.0 BentoML versions and are being migrated to the new 1.0 API. In the meantime, users may use Custom Models as a workaround.

• EvalML

• FastText

• Flax

• Gluon

• H2O

• Jax

• Neuropod

• ONNX-MLIR

• PaddlePaddle

• PyCaret

• PyTorch ignite

• SnapML

• Spacy

• Spark MLlib

• Statsmodels

Help us improve the project!

Found an issue or a TODO item? You’re always welcome to make contributions to the project and its documentation. Check out the BentoML development guide and documentation guide to get started.