BentoML Examples 🎨

BentoML is an open platform for machine learning in production. It simplifies model packaging and model management, optimizes model serving workloads to run at production scale, and accelerates the creation, deployment, and monitoring of prediction services.

The repository contains a collection of example projects demonstrating BentoML usage and best practices.

👉 Pop into our Slack community! We're happy to help with any issue you face or even just to meet you and hear what you're working on :)

Index

Example	Framework	Model	Functionality
custom_model_runner	PyTorch	MNIST	Custom Model Runner, Prometheus, gRPC
custom_python_model/lda_classifier	Picklable	LDA	Custom Python Model
custom_python_model/simple_pickable_model	Picklable	Python Function
custom_runner/nltk_pretrained_model	Custom	NLTK	Custom Runner
custom_runner/torch_hub_yolov5	Custom	YOLOv5	Custom Runner, Torch Hub
custom_web_serving/fastapi_example	SKLearn	Classification	FastAPI
custom_web_serving/flask_example	SKLearn	Classification	Flask
inference_graph	Transformers	Text Generation, Text Classification	Hugging Face Model Hub, Inference Graph
kfserving	SKLearn	Classification	KServe
mlflow/keras	MLflow, Keras	Sequential
mlflow/lightgbm	MLflow, LightGBM	Classification
mlflow/pytorch	MLflow, PyTorch	MNIST
mlflow/sklearn_autolog	MLflow, SKLearn	Linear Regression, Pipeline	MLflow Automatic Logging
mlflow/sklearn_logistic_regression	MLflow, SKLearn	Logistic Regression
mlflow/torchscript/IrisClassification	MLflow, TorchScript	Classfication	MLflow Log Model
mlflow/torchscript/MNIST	MLflow, PyTorch	MNIST	MLflow Log Model
monitoring/task_classification	SKLearn	Classfication	Model Monitoring, Classification Tasks
pydantic_validation	SKLearn	Classification	Pydantic Model, Validation
pytorch_mnist	PyTorch	MNIST
quickstart	SKLearn	Classification	Notebook
sklearn/linear_regression	SKLearn	Linear Regression
sklearn/pipeline	SKLearn	Pipeline
tensorflow2_keras	TensorFlow, Keras	MNIST	Notebook
tensorflow2_native	TensforFlow	MNIST	Notebook
xgboost	XGBoost	DMatrix
flax/MNIST	Flax	MNIST	gRPC, Testing
triton/onnx	ONNX	YOLOv5	Triton Inference Server, gRPC, Python SDK (Containerization, Serve, Build)
triton/pytorch	Torchscript	YOLOv5	Triton Inference Server, gRPC, Python SDK (Containerization, Serve, Build)
triton/tensorflow	Tensorflow	YOLOv5	Triton Inference Server, gRPC, Python SDK (Containerization, Serve, Build)
kubeflow	XGBoost	Fraud Detection	Kubeflow, Notebook

How to contribute

If you have issues running these projects or have suggestions for improvement, use Github Issues 🐱

If you are interested in contributing new projects to this repo, let's talk 🥰 - Join us on Slack and share your idea in #bentoml-contributors channel

Before you create a Pull Request, make sure:

• Follow the basic structures and naming conventions of other existing example projects
• Ensure your project runs with the latest version of BentoML

For legacy version prior to v1.0.0, see the 0.13-LTS branch.