Update README.md

Author: Koldim2001

README.md

@@ -4,7 +4,7 @@ This Python library simplifies SAHI-like inference for instance segmentation tas
 
 The library also provides a sleek customization of the visualization of the inference results for all models, both in the standard approach (direct network run) and the unique patch-based variant.
 
-**Model Support**: The library offers support for multiple ultralytics deep learning models, such as YOLOv8, YOLOv8-seg, YOLOv9, YOLOv9-seg, YOLOv10, FastSAM, and RTDETR. Users can select from pre-trained options or utilize custom-trained models to best meet their task requirements.
+**Model Support**: The library offers support for multiple ultralytics deep learning [models](https://docs.ultralytics.com/models/), such as YOLOv8, YOLOv8-seg, YOLOv9, YOLOv9-seg, YOLOv10, FastSAM, and RTDETR. Users can select from pre-trained options or utilize custom-trained models to best meet their task requirements.
 
 ## Installation
 You can install the library via pip:
@@ -220,7 +220,7 @@ classes_ids=result.filtered_classes_id
 classes_names=result.filtered_classes_names
 ```
 
-An example of working with this mode is presented in Google Color notebook - [![Open In Colab][colab_badge]][colab_ex1_memory_optimize]
+An example of working with this mode is presented in Google Colab notebook - [![Open In Colab][colab_badge]][colab_ex1_memory_optimize]
 
 [nb_example1]: https://nbviewer.org/github/Koldim2001/YOLO-Patch-Based-Inference/blob/main/examples/example_patch_based_inference.ipynb
 [colab_badge]: https://colab.research.google.com/assets/colab-badge.svg