Fix arg names in docs

docs/source/finetune.rst

@@ -13,7 +13,7 @@ You can fine-tune from an existing model by simply adding an argument to the CLI
 
 .. code-block:: console
 
-    spotiflow-train /path/to/spots_data --save-dir /my/trained/model --pretrained-model general
+    spotiflow-train /path/to/spots_data -o /my/trained/model --finetune-from general
 
 where `/path/to/pretrained/model` is the path to the directory containing the model you want to fine-tune. You can also pass other parameters to the training, such as the number of epochs, the learning rate, etc. For more information on the arguments allowed, see the documentation of the CLI command:
 
@@ -47,4 +47,4 @@ Finetuning a pre-trained model on a custom dataset is very easy. You can load th
     )
 
 Of course, you can also fine-tune from a model you have trained before. In that case, use the ``from_folder()`` method instead of ``from_pretrained()`` (see :ref:`index:Predicting spots in an image`).
-All the information about training customization from :ref:`train:Customizing the training` applies here as well. However, note that you cannot change the model architecture when fine-tuning!
+All the information about training customization from :ref:`train:Customizing the training` applies here as well. However, note that you cannot change the model architecture when fine-tuning!