Update README.md

README.md

@@ -31,26 +31,30 @@ There are two tutorial notebooks:
    2. load your sorting depending on the spike sorter you used to create the 'sorting' object
    3. Then you can create a Sorting_Analyzer object and you compute quality metrics.
 
-  auto_label_units is the main in this notebook. Link to API to know the parameters:
+  auto_label_units is the main in this notebook. API link to know the parameters:
   (https://spikeinterface--2918.org.readthedocs.build/en/2918/api.html#spikeinterface.curation.auto_label_units)
     
 
-   ``` python
+   
     from spikeinterface.curation import auto_label_units
    
     labels = auto_label_units(
     sorting_analyzer = sorting_analyzer,
     model_folder = “SpikeInterface/a_folder_for_a_model”,
     trusted = [‘numpy.dtype’])
-    ```
+
+    
 
 
-3. Train_new_model.ipynb
+2. Train_new_model.ipynb
 
    If you have your own manually curated data (e.g., from other species), this notebook allows you to train a new model using your specific data.
+   Here you need to follow the three steps mentioned before but you need to provide your manually curated labels.
 
+  train_model is the main function to do train your model. API Link:
+  https://spikeinterface--2918.org.readthedocs.build/en/2918/api.html#spikeinterface.curation.train_model
 
-   ``` python
+   
     from spikeinterface.curation.train_manual_curation import train_model
   
     trainer = train_model(mode = "analyzers",
@@ -59,10 +63,10 @@ There are two tutorial notebooks:
     output_folder = str(output_folder), 
     imputation_strategies = None, 
     scaling_techniques = None,
-    classifiers = None, # Default to Random Forest only. Other classifiers you can try [ "AdaBoostClassifier", "GradientBoostingClassifier",
+    classifiers = None) # Default to Random Forest only. Other classifiers you can try [ "AdaBoostClassifier", "GradientBoostingClassifier",
                                                                 # "LogisticRegression", "MLPClassifier", "XGBoost", "LightGBM", "CatBoost"]
-    )
-    ```
+    
+   
 
 Acknowledgments: