diff --git a/doc/finetuned_models.md b/doc/finetuned_models.md
index 4fc9fb13..ceedfc71 100644
--- a/doc/finetuned_models.md
+++ b/doc/finetuned_models.md
@@ -26,8 +26,8 @@ See for example the [2d annotator example](https://github.com/computational-cell
 
 As a rule of thumb:
 - Use the `_lm` models for segmenting cells or nuclei in light microscopy.
-- Use the `_em` models for segmenting ceells or neurites in electron microscopy.
-    - Note that this model does not work well for segmenting mitochondria or other organelles becuase it is biased towards segmenting the full cell / cellular compartment.
+- Use the `_em` models for segmenting cells or neurites in electron microscopy.
+    - Note that this model does not work well for segmenting mitochondria or other organelles because it is biased towards segmenting the full cell / cellular compartment.
 - For other cases use the default models.
 
 See also the figures above for examples where the finetuned models work better than the vanilla models.
diff --git a/doc/python_library.md b/doc/python_library.md
index dbab4b0a..7ab07b12 100644
--- a/doc/python_library.md
+++ b/doc/python_library.md
@@ -6,8 +6,8 @@ import micro_sam
 ```
 
 The library
-- implements function to apply Segment Anything to 2d and 3d data more conviently in `micro_sam.prompt_based_segmentation`.
-- provides more and imporoved automatic instance segmentation functionality in `micro_sam.instance_segmentation`.
+- implements function to apply Segment Anything to 2d and 3d data more conveniently in `micro_sam.prompt_based_segmentation`.
+- provides more and improved automatic instance segmentation functionality in `micro_sam.instance_segmentation`.
 - implements training functionality that can be used for finetuning on your own data in `micro_sam.training`.
 - provides functionality for quantitative and qualitative evaluation of Segment Anything models in `micro_sam.evaluation`.