Update README.md

README.md

@@ -56,7 +56,7 @@ print(predictions) # -> [0 -1]
 The computation is subdivided in two tasks (embedding, classification) to simplify a custom fine-tuning process.
 
 If you want to further optimize this classification head, you might want to deepcopy the layers and continue training 
-(of course one can choose which layers to pick with parameters start and end):
+(one can choose which layers by slicing the list):
 ```python
 import torch
 import copy
@@ -91,8 +91,6 @@ ISPIn(
 )
 ```
 
-If you want to take 
-
 ## Evaluation results
 |                 Dataset                | Metric       | Performance |
 |:--------------------------------------:|--------------|-------------|