Update README.md

README.md

@@ -7,6 +7,8 @@ tags:
 - Sentiment Analysis
 - Language Models
 ---
+# DistilSenti-Net42M: Context Distilled Small Language Model For Sentiment Analysis
+
 ## Model Architecture
 - **Embedding Layer**: Converts input text into dense vectors.
 - **CNN Layers**: Extracts features from text sequences.
@@ -69,7 +71,7 @@ from tensorflow.keras.models import load_model
 model_hybrid = load_model('< DistilSentiNet-42M.h5 File Path > or < DistilSentiNet-42M.keras File Path >')
 
 # Sample data
-df = pd.read_csv("./train.csv")
+df = pd.read_csv("<Your Test Dataset>")
 
 # Preprocessing
 df['text'] = df['text'].str.lower().str.replace('[^\w\s]', '', regex=True)