slight formatting error

tutorials/docs-16-external-samplers/external-samplers.jmd

@@ -32,7 +32,7 @@ Now we sample the model to generate some observations, which we can then conditi
 
 ```julia
 (; x) = rand(funnel() | (θ=0,))
-model = funnel() | (; x)
+model = funnel() | (; x);
 ```
 
 Users can use any sampler algorithm to sample this model if it follows the `AbstractMCMC` API.
@@ -56,7 +56,7 @@ Sampling is then as easy as:
 chain = sample(model, externalsampler(rwmh), 10_000)
 ```
 
-## Going beyond the `Turing` API
+## Going beyond the Turing API
 
 As previously mentioned, the Turing wrappers can often limit the capabilities of the sampling libraries they wrap.
 `AdvancedHMC`[^1] ((`AdvancedHMC`'s GitHub)[https://github.com/TuringLang/AdvancedHMC.jl]) is a clear example of this. A common practice when performing HMC is to provide an initial guess for the mass matrix.