diff --git a/README.md b/README.md
index 8f74809a41953cadfb1e83946a1ce56f0bd450a4..cb42b7cae7421e2ebda8526fbba0889afd763523 100644
--- a/README.md
+++ b/README.md
@@ -5,6 +5,9 @@ HSI Neural Networks
 
 [2] Blok, M., Banaś, J., & Pietrołaj, M. (2022). Strategie treningu neuronowego estymatora częstotliwości tonu krtaniowego z użyciem generatora syntetycznych samogłosek. Przegląd Telekomunikacyjny+ Wiadomości Telekomunikacyjne, 604-607.
 
+**NOTE:** The below instructions are outdated and relate to the previous versions of the project.
+The latest instructions (in Polish) are available on projects Wiki page: https://git.pg.edu.pl/ife/IFE_raw_base/-/wikis/home
+
 # Requirements & installation:
 1. Install Miniconda3 for Windows: https://docs.conda.io/en/latest/miniconda.html
 2. Create new conda environment:
@@ -13,10 +16,9 @@ HSI Neural Networks
 3. Install Pytorch on your active environment:
       - use command: <i>conda install pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch</i>
 4. Install additional python modules with requirement.txt file from this repository:
-      - *???* use command: <i>pip install -r requirements.txt</i>
       - use command: <i>conda install -c conda-forge --file requirements.txt</i>
 
- Once the above steps are completed, the environment is ready to be run.
+Once the above steps are completed, the environment is ready to be run.
 
  # Project overview
 
@@ -54,21 +56,3 @@ The below files can be treated as examples of proper usage of the scripts:
 # Usage
 
 To run the chosen script chose execute it under previously created (and active) conda environment. Use command: <i>python \<script-name></i>example: <i>python prepare_data.py</i>. All paths should be set directly in the script file.
-
-# Additional files
-
-Below are the links to data that is not stored in the repository. These files can be used for running the steps explained in the previous section.
-
-1. Data preparation:
-- [*.dat file with raw data](https://pgedupl-my.sharepoint.com/:u:/g/personal/s119424_o365_student_pg_edu_pl/EZf6b_0dSHlOlM5mLlXyWHwBwULDCxfn5jE0_lK2jWhV3g?e=dagyw2)
-- [*csv file with matching labels](https://pgedupl-my.sharepoint.com/:x:/g/personal/s119424_o365_student_pg_edu_pl/EWRMzbjnN2RGk_-5V5fcbd4B1Q68NLJkjE5av_mXgjgPzQ?e=hOhSfO)
-
-2. Training step:
-- [*.csv with training data - linear, 100 classes <50,400> Hz](https://pgedupl-my.sharepoint.com/:x:/g/personal/s119424_o365_student_pg_edu_pl/EfIZuLECXARCl7JVT99z8ZgBdeJ1mz6HDuBmURf2wOY2MQ?e=wChc4X)
-
-3. Inference step:
-- [*.csv with synthetic evaluation data - linear, 100 classes <50,400> Hz](https://pgedupl-my.sharepoint.com/:x:/g/personal/s119424_o365_student_pg_edu_pl/EdFaTCyEMphDnNOz4gi82dAB0fh0z2NDFtzfSGhpraK_ig?e=lphWxu)
-- [*.csv with speech evaluation data - linear, 100 classes <50,400> Hz](https://pgedupl-my.sharepoint.com/:x:/g/personal/s119424_o365_student_pg_edu_pl/ESh8NF5cw8hIvuICRVa7qiABEzPZAvL2gSkhDa64rpafxg?e=Xx3gyB)
-- [binary with already trained model - ~80% of accuracy](https://pgedupl-my.sharepoint.com/:u:/g/personal/s119424_o365_student_pg_edu_pl/EZGevrxyYxRKg9gYTW3PSSYBV6YCfdg06Nxhpn4Knp8pXg?e=cOtXLN)
-	
-All files can be also found here: [Additional files](https://pgedupl-my.sharepoint.com/:f:/g/personal/s119424_o365_student_pg_edu_pl/ElmX25HbIKRJgVeHDqFmoaMBDqipqVyQZHn4HbEDQajRNQ?e=1ltbkQ)