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MLOps 与训练MLOps & Training

45个工具 · 5个子类别

围绕模型生命周期的工程实践——实验跟踪、微调与 RLHF、流水线编排、模型注册表，以及一切所依赖的核心 ML 框架。

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Experiment Tracking & CI/CD8

CML
CML
Comet ML
Comet ML
DVC
DVC
GitHub Actions
GitHub Actions
GitLab CI
GitLab CI
MLflow
MLflow
Neptune
Neptune
Weights & Biases
Weights & Biases

Fine-tuning & RLHF4

Axolotl
Axolotl
O
OpenRLHF
TRL
TRL
unsloth
unsloth

Pipeline Orchestration4

AA
Apache Airflow
Kubeflow
Kubeflow
Prefect
Prefect
ZenML
ZenML

Model Registry & Feature Store6

Feast
Feast
Hopsworks
Hopsworks
Hugging Face Hub
Hugging Face Hub
MLflow Model Registry
MLflow Model Registry
Tecton
Tecton
Vertex Feature Store
Vertex Feature Store

ML Frameworks23

Accord.NET
Accord.NET
Alink
Alink
Angel-ML
Angel-ML
AS
Auto-sklearn
AutoGluon
AutoGluon
Diffusers
Diffusers
FLAML
FLAML
Google AutoML
Google AutoML
H2O AutoML
H2O AutoML
Hugging Face Transformers
Hugging Face Transformers
J
JAX
Keras
Keras
L
LightGBM
MO
Mixture of Kittens
OpenAI Gym
OpenAI Gym
OpenAI Python SDK
OpenAI Python SDK
PettingZoo
PettingZoo
PyTorch
PyTorch
Ray RLlib
Ray RLlib
scikit-learn
scikit-learn
SB
Stable Baselines3
TensorFlow
TensorFlow
X
XGBoost
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