Update .pre-commit-config.yaml (#1026)

docs/cli.md

@@ -92,7 +92,7 @@ Export a YOLOv8n model to a different format like ONNX, CoreML, etc.
 
 ## Overriding default arguments
 
-Default arguments can be overriden by simply passing them as arguments in the CLI in `arg=value` pairs.
+Default arguments can be overridden by simply passing them as arguments in the CLI in `arg=value` pairs.
 
 !!! tip ""
 

docs/predict.md

@@ -96,7 +96,7 @@ Class reference documentation for `Results` module and its components can be fou
 
 ## Visualizing results
 
-You can use `visualize()` function of `Result` object to get a visualization. It plots all componenets(boxes, masks, classification logits, etc) found in the results object
+You can use `visualize()` function of `Result` object to get a visualization. It plots all components(boxes, masks, classification logits, etc) found in the results object
 ```python
     res = model(img)
     res_plotted = res[0].visualize()

docs/python.md

@@ -2,7 +2,7 @@ The simplest way of simply using YOLOv8 directly in a Python environment.
 
 !!! example "Train"
 
-    === "From pretrained(recommanded)"
+    === "From pretrained(recommended)"
         ```python
         from ultralytics import YOLO