Update README.md

README.md

@@ -1,9 +1,18 @@
----
-license: cc-by-sa-4.0
-datasets:
-- GiliGold/VAD_KnessetCorpus
-- HaifaCLGroup/KnessetCorpus
----
+---
+license: cc-by-sa-4.0
+datasets:
+- GiliGold/VAD_KnessetCorpus
+- HaifaCLGroup/KnessetCorpus
+language:
+- he
+tags:
+- vad
+- valence
+- arousal
+- dominance
+- regression
+- knesset
+---
 # VAD Binomial Regression Models
 This repository contains three binomial regression models designed to predict VAD (Valence, Arousal, Dominance) scores for text inputs. 
 Each model is stored as a separate pickle (.pkl) file:
@@ -11,6 +20,7 @@ Each model is stored as a separate pickle (.pkl) file:
 - **valence_model.pkl**: Predicts the Valence score (positivity/negativity).
 - **arousal_model.pkl**: Predicts the Arousal score (level of excitement or calm).
 - **dominance_model.pkl**: Predicts the Dominance score (sense of control or influence).
+
 All scores are normalized on a scale from 0 to 1.
 
 Before making predictions, input text must be converted into embeddings using the [Knesset-multi-e5-large](https://huggingface.co/GiliGold/Knesset-multi-e5-large) model. The embeddings are then fed into the regression models.
@@ -55,5 +65,4 @@ with open(model_v_path, "rb") as f:
 valence_score = valence_model.predict([embedding_vector])
 
 print(f"Predicted Valence Score: {valence_score[0]}")
-```
-
+```