diff --git a/README.md b/README.md
index 6b7d47ef295c4806eac75aee63deaac27d59265b..89beb0788f509e2601acb040fbfa0b6111b958a9 100644
--- a/README.md
+++ b/README.md
@@ -46,7 +46,7 @@ Among the repository files is pre-prepared `docker-compose.yml` file which conta
 In Your terminal navigate to the folder where the files from the repository are downloaded and execute the following command:
 
 ```shell
-docker compose run movement-classification R --quiet -e "rmarkdown::render('get_features.Rmd')"
+docker compose run movement-classification R --quiet -e "rmarkdown::render('get_features.Rmd', output_file = '/output/features.html')"
 ```
 
 By default input dat are downloaded into a folder `data_zenodo` and output features are also placed into this folder.
@@ -58,7 +58,7 @@ In case You have not run the first step, in this step features are downloaded fr
 In Your terminal navigate to the folder where the files from the repository are downloaded and execute the following command:
 
 ```shell
-docker compose run movement-classification R --quiet -e "rmarkdown::render('get_results.Rmd')"
+docker compose run movement-classification R --quiet -e "rmarkdown::render('get_results.Rmd', output_file = '/output/classification.html')"
 ```
 
 The results are HTML document placed into the folder `output`.
@@ -108,7 +108,7 @@ reticulate::virtualenv_install("hmch", c("-r", "requirements.txt"))
 Now You can execute the script by calling
 
 ```bash
-R -e "rmarkdown::render(get_features.Rmd, output_file = '/output/features.html')"
+R -e "rmarkdown::render(get_features.Rmd)"
 ```
 
 ## Step 2 Classification
@@ -127,7 +127,7 @@ renv::restore()
 ### Model execution
 
 ```bash
-R -e "rmarkdown::render(get_results.Rmd, output_file = '/output/classification.html')"
+R -e "rmarkdown::render(get_results.Rmd)"
 ```
 
 At the same time this file reproduce figures from an article which is now under review and later we will link it when it is published.