docs: add fmpe to tutorials, fix docstrings

sbi/neural_nets/factory.py

@@ -223,8 +223,8 @@ def flowmatching_nn(
     be used for Flow Matching. The returned function is to be passed to the
 
     Args:
-        model: The type of density estimator that will be created. One of [`mdn`,
-            `made`, `maf`, `maf_rqs`, `nsf`].
+        model: the type of regression network to learn the vector field. One of ['mlp',
+            'resnet'].
         z_score_theta: Whether to z-score parameters $\theta$ before passing them into
             the network, can take one of the following:
             - `none`, or None: do not z-score.
@@ -239,9 +239,8 @@ def flowmatching_nn(
             density estimator is a normalizing flow (i.e. currently either a `maf` or a
             `nsf`). Ignored if density estimator is a `mdn` or `made`.
         num_blocks: Number of blocks if a ResNet is used.
-        embedding_net: Optional embedding network for x.
-        num_components: Number of mixture components for a mixture of Gaussians.
-            Ignored if density estimator is not an mdn.
+        num_frequencies: Number of frequencies for the time embedding.
+        embedding_net: Optional embedding network for the condition.
         kwargs: additional custom arguments passed to downstream build functions.
     """
     implemented_models = ["mlp", "resnet"]