docs: point multi-dataset example links at the renamed multi_dataset package

The `multi` example package in autogalaxy_workspace is renamed to
`multi_dataset` (autogalaxy_workspace#408). This updates the doc links and
prose that point into it.

Docs-only — no library source touched.

`bound: multi` in the non_linear.yaml configs is a Dynesty search
kwarg and is deliberately left alone.

MERGE ORDER: this must merge *after* the autogalaxy_workspace rename PR,
since these are `blob/main` URLs that 404 until the package moves.

Refs PyAutoLabs/autolens_workspace#408

Author: Jammy2211

docs/general/model_cookbook.md

@@ -242,7 +242,7 @@ but certain parameters are free to vary across the datasets.
 
 The following example notebooks show how to compose and fit these models:
 
-<https://github.com/PyAutoLabs/autogalaxy_workspace/blob/main/notebooks/multi/start_here.ipynb>
+<https://github.com/PyAutoLabs/autogalaxy_workspace/blob/main/notebooks/multi_dataset/start_here.ipynb>
 
 ## Relations (Advanced)
 
@@ -251,7 +251,7 @@ We can compose models where the free parameter(s) vary according to a user-speci
 
 The following example notebooks show how to compose and fit these models:
 
-<https://github.com/PyAutoLabs/autogalaxy_workspace/blob/main/notebooks/multi/features/wavelength_dependence/modeling.ipynb>
+<https://github.com/PyAutoLabs/autogalaxy_workspace/blob/main/notebooks/multi_dataset/features/wavelength_dependence/modeling.ipynb>
 
 ## PyAutoFit API
 

docs/overview/overview_2_new_user_guide.md

@@ -40,7 +40,7 @@ You now need to decide what type of data you are interested in:
 
 - **CDD Imaging**: For image data from telescopes like Hubble and James Webb, go to [imaging/start_here.ipynb](https://github.com/PyAutoLabs/autogalaxy_workspace/blob/main/notebooks/imaging/start_here.ipynb).
 - **Interferometer**: For radio / sub-mm interferometer from instruments like ALMA, go to [interferometer/start_here.ipynb](https://github.com/PyAutoLabs/autogalaxy_workspace/blob/main/notebooks/interferometer/start_here.ipynb).
-- **Multi-Band Imaging**: For galaxies observed in multiple wavebands go to [multi/start_here.ipynb](https://github.com/PyAutoLabs/autogalaxy_workspace/blob/main/notebooks/multi/start_here.ipynb).
+- **Multi-Band Imaging**: For galaxies observed in multiple wavebands go to [multi_dataset/start_here.ipynb](https://github.com/PyAutoLabs/autogalaxy_workspace/blob/main/notebooks/multi_dataset/start_here.ipynb).
 
 ## Google Colab
 
@@ -54,7 +54,7 @@ so you can check it is the right software for you before going through the insta
   Galaxy modeling with CCD imaging (e.g. Hubble, James Webb, ground-based telescopes).
 - [interferometer/start_here.ipynb](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.29.2/notebooks/interferometer/start_here.ipynb):
   Galaxy modeling with interferometer data (e.g. ALMA), fitting directly in the uv-plane.
-- [multi_band/start_here.ipynb](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.29.2/notebooks/multi/start_here.ipynb):
+- [multi_band/start_here.ipynb](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.29.2/notebooks/multi_dataset/start_here.ipynb):
   Multi-band galaxy modeling to study colour gradients and wavelength-dependent structure.
 - [multi_galaxy/start_here.ipynb](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.29.2/notebooks/multi_galaxy/start_here.ipynb):
   Blended multi-galaxy systems — one free light model per galaxy, fitted simultaneously.

docs/overview/overview_3_features.md

@@ -57,7 +57,7 @@ The appearance of the galaxy changes as a function of wavelength, therefore mult
 more about the different components in a galaxy (e.g a redder bulge and bluer disk) or when imaging and interferometer
 data are combined, we can compare the emission from stars and dust.
 
-Checkout the `autogalaxy_workspace/*/multi` package to get started, however combining datasets is a more advanced
+Checkout the `autogalaxy_workspace/*/multi_dataset` package to get started, however combining datasets is a more advanced
 feature and it is recommended you first get to grips with the core API.
 
 ## Ellipse Fitting