Integrations & Tutorials: Revamp

docs.json

@@ -411,118 +411,47 @@
                       {
                         "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/integrations/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_transformers",
                           "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"
                     ]
                   }
                 ]
               },
-              {
-                "group": "Tutorials",
-                "pages": [
-                  "models/tutorials",
-                  {
-                    "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"
-                    ]
-                  },
-                  {
-                    "group": "Advanced Tutorials",
-                    "pages": [
-                      "models/tutorials/monai_3d_segmentation",
-                      "models/tutorials/volcano",
-                      "models/tutorials/minikube_gpu"
-                    ]
-                  }
-                ]
-              },
               {
                 "group": "Reference",
                 "pages": [
@@ -3794,7 +3723,7 @@
     {
       "source": "/library/init",
       "destination": "/models/ref/python/functions/init"
-    },
+    },    
     {
       "source": "/models/app/pages/workspaces",
       "destination": "/models/app/features/cascade-settings"
@@ -3810,6 +3739,83 @@
     {
       "source": "/models/integrations/openai",
       "destination": "/models/integrations/openai-api"
+
+    },
+    {
+      "source": "/models/tutorials",
+      "destination": "/models/integrations"
+    },
+    {
+      "source": "/models/tutorials/huggingface",
+      "destination": "/models/integrations/huggingface"
+    },
+    {
+      "source": "/models/tutorials/minikube_gpu",
+      "destination" : "/models/integrations"
+    },    
+    {
+      "source": "/models/tutorials/monai_3d_segmentation",
+      "destination": "/models/integrations"
+    },
+    {
+      "source": "/models/tutorials/lightning",
+      "destination": "/models/integrations/lightning"
+    },
+    {
+      "source": "/models/tutorials/tensorflow",
+      "destination": "/models/integrations/tensorflow"
+    },
+    {
+      "source" : "/models/tutorials/tensorflow_sweeps",
+      "destination": "/models/sweeps"
+    },    
+    {
+      "source" : "/models/tutorials/xgboost_sweeps",
+      "destination": "/models/sweeps"
+    },
+    {
+      "source":"/models/tutorials/volcano",
+      "destination": "/models/integrations"
+    },
+    {
+      "source": "/models/tutorials/weave_models_registry",
+      "destination": "/models/integrations"
+    },
+    {
+      "source": "/models/tutorials/pytorch",
+      "destination": "/models/integrations/pytorch"
+    },
+    {
+      "source": "/models/tutorials/artifacts",
+      "destination": "/models/tutorials"
+    },
+    {
+      "source": "/models/tutorials/experiments",
+      "destination": "/models/tutorials"
+    },
+    {
+      "source": "/models/tutorials/keras",
+      "destination": "/models/tutorials"
+    },
+    {
+      "source": "/models/tutorials/keras_models",
+      "destination": "/models/tutorials"
+    },
+    {
+      "source": "/models/tutorials/keras_tables",
+      "destination": "/models/tutorials"
+    },
+    {
+      "source": "/models/tutorials/sweeps",
+      "destination": "/models/tutorials"
+    },
+    {
+      "source": "/models/tutorials/tables",
+      "destination": "/models/tutorials"
+    },
+    {
+      "source": "/models/tutorials/workspaces",
+      "destination": "/models/tutorials"
     },
     {
       "source": "/models/ref/python/init",
@@ -3831,6 +3837,10 @@
       "source": "models/support/rotate_revoke_access",
       "destination": "/models/support/find_api_key"
     },
+    {
+      "source": "/models/evaluate-models",
+      "destination": "/models/tables/evaluate-models"
+    },
     {
       "source": "/models/track/launch/*",
       "destination": "/platform/launch"

models.mdx

@@ -18,4 +18,6 @@ With W&B Models, you can:
 - [Maintain a centralized hub of all models](/models/registry/), with a seamless handoff point to devops and deployment
 - Configure custom automations that trigger key workflows for [model CI/CD](/models/automations/).
 
-Machine learning practitioners rely on W&B Models as their ML system of record to track and visualize experiments, manage model versions and lineage, and optimize hyperparameters.
+Machine learning practitioners rely on W&B Models as their ML system of record to track and visualize experiments, manage model versions and lineage, and optimize hyperparameters.
+
+{/* Learn how to fine-tune a model with W&B Models and Weave in this [Colab notebook](https://colab.research.google.com/drive/1Uqgel6cNcGdP7AmBXe2pR9u6Dejggsh8?usp=sharing). */}

models/artifacts.mdx

@@ -6,7 +6,7 @@ import { ColabLink } from '/snippets/en/_includes/colab-link.mdx';
 import { TryProductLink } from '/snippets/en/_includes/try-product-link.mdx';
 
 <CardGroup cols={4}>
-<ColabLink url="https://colab.research.google.com/github/wandb/examples/blob/master/colabs/wandb_registry/zoo_wandb.ipynb" />
+<ColabLink url="https://colab.research.google.com/github/wandb/examples/blob/master/colabs/wandb-artifacts/Pipeline_Versioning_with_W&B_Artifacts.ipynb" />
 <TryProductLink url="https://wandb.ai/wandb/arttest/artifacts/model/iv3_trained/5334ab69740f9dda4fed/lineage" />
 </CardGroup>
 

models/integrations.mdx

@@ -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.