# Tutorials

Step-by-step notebooks covering the main workflows of NetKet Foundation.

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:gutter: 2

:::{grid-item-card} 1. FNQS Training Basics
:link: 1.%20FNQS%20training%20basics.html
:link-type: url

A first look at NetKet Foundation: setting up a model, defining a parameter space, and running a basic optimization.
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:::{grid-item-card} 2. FNQS with Disorder
:link: 2.%20FNQS%20with%20disorder.html
:link-type: url

Training foundation neural quantum states on disordered Hamiltonians.
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:::{grid-item-card} 3. Importance Sampling
:link: 3.%20Importance%20Sampling.html
:link-type: url

Using importance sampling to improve training efficiency.
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:::{grid-item-card} 4. Managing Data with FNQS
:link: 4.%20Managing%20data%20with%20FNQS.html
:link-type: url

How to handle datasets and checkpoints when working with FNQS.
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:::{grid-item-card} 5. Hubbard model with FNQS
:link: 5.%20Hubbard%20model%20with%20FNQS.html
:link-type: url

Training a fermionic foundation NQS on the 1D Hubbard chain across the full U/t range.
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```{toctree}
:hidden:
:maxdepth: 1

1. FNQS training basics
2. FNQS with disorder
3. Importance Sampling
4. Managing data with FNQS
5. Hubbard model with FNQS
```