text update

app.py

@@ -51,9 +51,9 @@ def make_plot(n_samples, n_features, n_tasks, n_relevant_features, alpha, progre
     
 model_card = f"""
 ## Description
-Multi-task Lasso allows us to jointly fit multiple regression problems  by enforcing the selected features to be the same across tasks. This example simulates sequential measurement. Each task
-is a time instant, and the relevant features, while being the same, vary in amplitude over time. Multi-task lasso imposes that features that are selected at one time point are selected
-for all time points. This makes feature selection more stable than by regular Lasso.
+Multi-task Lasso allows us to jointly fit multiple regression problems  by enforcing the selected features to be the same across tasks. This example simulates sequential measurement. 
+Each task is a time instant, and the relevant features, while being the same, vary in amplitude over time. Multi-task lasso imposes that features that are selected at one time point 
+are selected for all time points. This makes feature selection more stable than by regular Lasso.
 ## Model
 currentmodule: sklearn.linear_model
 class:`Lasso` and class: `MultiTaskLasso` are used in this example.