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Integrations & Tutorials: Revamp TOC POC #1954

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first draft
ngrayluna Dec 2, 2025
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Remove duplicates
ngrayluna Dec 2, 2025
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Merge branch 'main' into integrations_tutorials_section_revamp_demo
ngrayluna Jan 26, 2026
8377cad
Added some integrations back
ngrayluna Jan 26, 2026
95f5111
update landing page descriptions
ngrayluna Jan 26, 2026
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Removed non HEX integrations
ngrayluna Jan 28, 2026
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Merge branch 'main' into integrations_tutorials_section_revamp_demo
ngrayluna Feb 2, 2026
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merge branch 'main' into integrations_tutorials_section_revamp_demo
ngrayluna Feb 3, 2026
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ngrayluna Feb 4, 2026
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ngrayluna Feb 4, 2026
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Merge branch 'main' into integrations_tutorials_section_revamp_demo
ngrayluna Feb 4, 2026
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194 changes: 141 additions & 53 deletions docs.json
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Original file line number Diff line number Diff line change
Expand Up @@ -411,72 +411,40 @@
{
"group": "ML Frameworks",
"pages": [
"models/integrations/catalyst",
"models/integrations/deepchem",
"models/integrations/dspy",
"models/integrations/keras",
"models/integrations/lightgbm",
"models/integrations/mmengine",
"models/integrations/mmf",
"models/integrations/paddledetection",
"models/integrations/paddleocr",
"models/tutorials/pytorch",
"models/integrations/lightning",
"models/integrations/ignite",
"models/integrations/skorch",
"models/integrations/tensorflow",
"models/integrations/xgboost"
]
},
{
"group": "ML Libraries",
"pages": [
"models/integrations/deepchecks",
"models/integrations/huggingface",
"/models/integrations/accelerate",
"models/integrations/diffusers",
"models/integrations/autotrain",
"models/integrations/fastai",
"models/integrations/fastai/v1",
"models/integrations/composer",
"models/integrations/simpletransformers",
"models/integrations/huggingface",
"models/integrations/openai-gym",
"models/integrations/prodigy",
"models/integrations/pytorch-geometric",
"models/integrations/torchtune",
"models/integrations/scikit",
"models/integrations/simpletransformers",
"models/integrations/spacy",
"models/integrations/stable-baselines-3",
"models/integrations/ultralytics"
"models/integrations/torchtune"
]
}
]
},
{
"group": "Cloud Platforms",
"pages": [
"models/integrations/sagemaker",
"models/integrations/databricks",
"models/integrations/azure-openai-fine-tuning",
"models/integrations/openai-fine-tuning",
"models/integrations/cohere-fine-tuning",
"models/integrations/openai-api",
"models/integrations/nim"
]
},
{
"group": "Workflow Orchestration",
"pages": [
"models/integrations/kubeflow-pipelines-kfp",
"models/integrations/metaflow",
"models/integrations/dagster",
"models/integrations/hydra"
"models/integrations/openai-api"
]
},
{
"group": "Other",
"pages": [
"models/integrations/docker",
"models/integrations/tensorboard",
"models/integrations/w-and-b-for-julia",
"models/integrations/hydra",
"models/integrations/yolox",
"models/integrations/yolov5"
]
Expand All @@ -490,27 +458,15 @@
{
"group": "Fundamentals",
"pages": [
"models/tutorials/experiments",
"models/tutorials/tables",
"models/tutorials/sweeps",
"models/tutorials/artifacts",
"models/tutorials/workspaces",
"models/tutorials/weave_models_registry",
"models/evaluate-models"
]
},
{
"group": "Framework Tutorials",
"pages": [
"models/tutorials/keras",
"models/tutorials/keras_models",
"models/tutorials/keras_tables",
"models/tutorials/pytorch",
"models/tutorials/lightning",
"models/tutorials/tensorflow",
"models/tutorials/tensorflow_sweeps",
"models/tutorials/xgboost_sweeps",
"models/tutorials/huggingface"
"models/tutorials/xgboost_sweeps"
]
},
{
Expand Down Expand Up @@ -2481,7 +2437,139 @@
},
{
"source": "/models/integrations/openai",
"destination": "/models/integrations/openai-api"
"destination": "/models/integrations"
},
{
"source": "/models/integrations/autotrain",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/catalyst",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/cohere-fine-tuning",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/composer",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/dagster",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/databricks",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/deepchecks",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/deepchem",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/docker",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/dspy",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/fastai",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/fastai/v1",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/hydra",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/kubeflow-pipelines-kfp",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/lightgbm",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/metaflow",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/mmengine",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/mmf",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/nim",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/openai-api",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/openai-gym",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/paddledetection",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/paddleocr",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/prodigy",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/pytorch-geometric",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/sagemaker",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/scikit",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/skorch",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/spacy",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/stable-baselines-3",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/tensorboard",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/ultralytics",
"destination": "/models/integrations"
},
{
"source": "/models/integrations/w-and-b-for-julia",
"destination": "/models/integrations"
},
{
"source": "/models/ref/python/init",
Expand Down
97 changes: 21 additions & 76 deletions models/integrations.mdx
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Expand Up @@ -5,79 +5,24 @@ description: Explore W&B integrations with ML frameworks, cloud platforms, and w

W&B integrates with popular machine learning frameworks, cloud platforms, and workflow orchestration tools to help you track experiments, log metrics, and manage models seamlessly.

## Getting started

If you're looking to integrate W&B with a library not listed here, see [Add W&B to any library](/models/integrations/add-wandb-to-any-library) for best practices and implementation guidance.

## ML frameworks and libraries

### ML frameworks

Integrate W&B with popular machine learning frameworks:

- [Catalyst](/models/integrations/catalyst)
- [DeepChem](/models/integrations/deepchem)
- [DSPy](/models/integrations/dspy)
- [Keras](/models/integrations/keras)
- [LightGBM](/models/integrations/lightgbm)
- [MMEngine](/models/integrations/mmengine)
- [MMF](/models/integrations/mmf)
- [PaddleDetection](/models/integrations/paddledetection)
- [PaddleOCR](/models/integrations/paddleocr)
- [PyTorch Lightning](/models/integrations/lightning)
- [PyTorch Ignite](/models/integrations/ignite)
- [Skorch](/models/integrations/skorch)
- [TensorFlow](/models/integrations/tensorflow)
- [XGBoost](/models/integrations/xgboost)

### ML libraries

Extend your workflow with these ML libraries:

- [Deepchecks](/models/integrations/deepchecks)
- [Hugging Face](/models/integrations/huggingface)
- [Diffusers](/models/integrations/diffusers)
- [AutoTrain](/models/integrations/autotrain)
- [Fast.ai](/models/integrations/fastai)
- [Fast.ai v1](/models/integrations/fastai/v1)
- [Composer](/models/integrations/composer)
- [OpenAI Gym](/models/integrations/openai-gym)
- [Prodigy](/models/integrations/prodigy)
- [PyTorch Geometric](/models/integrations/pytorch-geometric)
- [TorchTune](/models/integrations/torchtune)
- [Scikit-learn](/models/integrations/scikit)
- [Simple Transformers](/models/integrations/simpletransformers)
- [spaCy](/models/integrations/spacy)
- [Stable Baselines 3](/models/integrations/stable-baselines-3)
- [Ultralytics](/models/integrations/ultralytics)

## Cloud platforms

Deploy and train models on cloud platforms with W&B:

- [Amazon SageMaker](/models/integrations/sagemaker)
- [Databricks](/models/integrations/databricks)
- [Azure OpenAI Fine-tuning](/models/integrations/azure-openai-fine-tuning)
- [OpenAI Fine-tuning](/models/integrations/openai-fine-tuning)
- [Cohere Fine-tuning](/models/integrations/cohere-fine-tuning)
- [OpenAI API](/models/integrations/openai-api)
- [NVIDIA NIM](/models/integrations/nim)

## Workflow orchestration

Integrate W&B with workflow orchestration tools:

- [Kubeflow Pipelines (KFP)](/models/integrations/kubeflow-pipelines-kfp)
- [Metaflow](/models/integrations/metaflow)
- [Dagster](/models/integrations/dagster)
- [Hydra](/models/integrations/hydra)

## Other integrations

Additional tools and integrations:

- [Docker](/models/integrations/docker)
- [TensorBoard](/models/integrations/tensorboard)
- [W&B for Julia](/models/integrations/w-and-b-for-julia)
- [YOLOX](/models/integrations/yolox)
- [YOLOv5](/models/integrations/yolov5)
## Popular ML integrations:

<CardGroup cols={2}>
<Card title="PyTorch Lightning" href="/models/integrations/lightning">
Integrate W&B with your PyTorch Lightning code to add experiment tracking to your pipeline.
</Card>
<Card title="HuggingFace Transformers" href="/models/integrations/huggingface">
Optimize HuggingFace Transformer models with W&B for experiment tracking and model management.
</Card>
</CardGroup>

<CardGroup cols={2}>
<Card title="Keras" href="/models/integrations/keras">
Use W&B and Keras for machine learning experiment tracking, dataset versioning, and project collaboration.
</Card>
<Card title="YOLOv5" href="/models/integrations/yolov5">
Use the "You Only Look Once" (aka YOLOv5) real-time object detection framework and W&B to track model metrics, inspect model outputs, and restart interrupted runs.
</Card>
</CardGroup>

If the library you use is not supported natively, you can still integrate W&B using the W&B [Python SDK](/docs/library/integrations/python-sdk). See [Add W&B to any library](/models/integrations/add-wandb-to-any-library) for best practices and implementation guidance.
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