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

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.

  • Detectron

  • EasyOCR

  • 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.