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BentoML

BentoML

  • Overview
    • What is BentoML?
    • Ecosystem
  • Quickstarts
    • Install BentoML
    • Deploy a Transformer model with BentoML
    • Deploy a large language model with OpenLLM and BentoML
    • Deploy an Iris classification model with BentoML
    • Deploy a YOLO model with BentoML
    • Deploy Stable Diffusion XL with dynamic LoRA adapters
  • Main Concepts
    • Models
    • Service and APIs
    • Building Bentos
    • Using Runners
    • Deploying Bento
  • Framework Guides
    • CatBoost
    • Diffusers
    • fast.ai
    • Keras
    • LightGBM
    • ONNX
    • Picklable Model
    • PyTorch
    • PyTorch Lightning
    • Scikit-Learn
    • EasyOCR
    • TensorFlow
    • Transformers
    • XGBoost
    • Detectron2
  • Advanced Guides
    • Adaptive Batching
    • Advanced Containerization
    • Bento Client
    • Bento Server
    • Configuration
    • Resource Scheduling Strategy
    • Environment Manager
    • GitHub Actions
    • Inference Graph
    • Inference Data Collection & Model Monitoring
    • Logging
    • Metrics
    • Performance Guide
    • Serving with gRPC
    • Serving with GPU
    • Security
    • Streaming
    • Tracing
    • 1.0 Migration Guide
  • Integrations
    • Airflow
    • Arize AI
    • Flink
    • Kubeflow
    • MLflow
    • Spark
    • Triton Inference Server
    • Ray
  • API Reference
    • Core Components
    • Bento Store APIs
    • API IO Descriptors
    • Metrics API
    • Framework APIs
      • Diffusers
      • ONNX
      • Scikit-Learn
      • Transformers
      • Flax
      • TensorFlow
      • TorchScript
      • XGBoost
      • Picklable Model
      • PyTorch
      • LightGBM
      • MLflow
      • CatBoost
      • fast.ai
      • EasyOCR
      • Keras
      • Ray
      • Detectron
    • BentoML CLI
    • Batch Inference
    • Exceptions
    • Container APIs
    • Types
  • Examples

BentoCloud

  • Get Started
    • Understand BentoCloud
    • Quickstart
  • How-to Guides
    • Deploy Bentos
    • Manage Access Tokens
    • Manage Models and Bentos
    • Manage Users
    • Monitor Events
  • Topic Guides
    • Observability
  • Best Practices
    • Cost Optimization
  • Reference
    • Deployment creation and update information
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v1.0.23
0.13-lts
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Framework APIs#

Note

This page contains the API reference for all frameworks. For more information on a specific framework, please see Framework Guides

Diffusers
ONNX
Scikit-Learn
Transformers
Flax
TensorFlow
XGBoost
Picklable Model
PyTorch
LightGBM
MLflow
CatBoost
fast.ai
Keras
Detectron
EasyOCR
Ray
Next
Diffusers
Previous
Metrics API
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