Update README.md

README.md

@@ -13,19 +13,8 @@ You can use this model directly with a pipeline for text classification:
 ```python
 >>> from transformers import pipeline
 >>> classifier = pipeline("text-classification", model="paulagarciaserrano/roberta-depression-detection")
->>> classifier ("I am very sad.")
-```
-
-Here is how to use this model with PyTorch:
-
-```python
-from transformers import AutoModelForSequenceClassification, AutoTokenizer
-model_checkpoint = "paulagarciaserrano/roberta-depression-detection"
-tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
-model = AutoModelForSequenceClassification.from_pretrained(model_checkpoint, num_labels=3)
-text = "I am very sad."
-encoded_input = tokenizer(text, return_tensors='pt')
-output = model(**encoded_input)
+>>> your_text = "I am very sad."
+>>> classifier (your_text)
 ```
 
 # Training and evaluation data