Update README.md

README.md

@@ -42,7 +42,7 @@ The SentimentClassifier model is designed to detect whether a given sentence is
 
 #### Intended Use
 
-The AgentClassifier model is intended to be used for the analysis of central bank communications where sentiment analysis is essential. 
+The SentimentClassifier model is intended to be used for the analysis of central bank communications where sentiment analysis is essential. 
 
 #### Performance
 
@@ -59,10 +59,10 @@ You can use these models in your own applications by leveraging the Hugging Face
 from transformers import pipeline
 
 # Load the SentimentClassifier model
-agent_classifier = pipeline("text-classification", model="Moritz-Pfeifer/CentralBankRoBERTa-sentiment-classifier")
+sentiment_classifier = pipeline("text-classification", model="Moritz-Pfeifer/CentralBankRoBERTa-sentiment-classifier")
 
 # Perform sentiment analysis
-sentinement_result = agent_classifier("The early effects of our policy tightening are also becoming visible, especially in sectors like manufacturing and construction that are more sensitive to interest rate changes.")
+sentinement_result = sentiment_classifier("The early effects of our policy tightening are also becoming visible, especially in sectors like manufacturing and construction that are more sensitive to interest rate changes.")
 print("Sentiment:", sentinement_result[0]['label'])
 ```