Update README.md

README.md

@@ -26,16 +26,16 @@ tokenizer = BertTokenizer.from_pretrained("bert-base-german-cased")
 Prepare Your Text:
 You can perform text classification with this model. Tokenize your text using the tokenizer:
 
-python
+# Enter Text Input
 text = "Deine Textnachricht hier"  # Your German text
-inputs = tokenizer(text, padding='max_length', truncation=True, max_length=128, return_tensors='tf', return_attention_mask=True)
+
 Get Predictions:
 Predict the label or class for your text:
+inputs = tokenizer(text, padding='max_length', truncation=True, max_length=128, return_tensors='tf', return_attention_mask=True)
 
-python
-with tf.device('/GPU:0'):
+# Make a prediction
+with tf.device('/GPU:0'):  # Specify the GPU device
     outputs = model(inputs)
-predicted_class = tf.argmax(outputs.logits, axis=1).numpy()[0]
 The predicted_class will give you the predicted label for your text.
 
 Semantic Search: