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Fix typo #656

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Jun 15, 2024
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Fix typo #656

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262 changes: 208 additions & 54 deletions examples/howto/blackbox_external_likelihood_numpy.ipynb
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2 changes: 1 addition & 1 deletion examples/howto/blackbox_external_likelihood_numpy.myst.md
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Expand Up @@ -64,7 +64,7 @@ Another issue is that if you want to be able to use the gradient-based step samp

Defining a model/likelihood that PyMC can use and that calls your "black box" function is possible, but it relies on creating a custom PyTensor Op. This is, hopefully, a clear description of how to do this, including one way of writing a gradient function that could be generally applicable.

In the examples below, we create a very simple lineral model and log-likelihood function in numpy.
In the examples below, we create a very simple linear model and log-likelihood function in numpy.

```{code-cell} ipython3
def my_model(m, c, x):
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