Update README.md

README.md

@@ -18,6 +18,9 @@ model-index:
       - task:
           type: text-generation
         metrics:
+          - name: Average 
+            type: Average
+            value: 72.75
           - name: ARC
             type: ARC
             value: 68.00
@@ -62,6 +65,8 @@ Spherical Linear Interpolation (SLERP) serves as a technique for seamlessly inte
 
 Opting for SLERP over traditional linear interpolation is motivated by various considerations. Linear interpolation in high-dimensional spaces may result in a reduction in the magnitude of the interpolated vector, diminishing the scale of weights. Additionally, in many cases, the alteration in the weights' direction conveys more meaningful information, such as feature learning and representation, compared to the magnitude of change.
 
+$$ {\displaystyle \operatorname {slerp} (p_{0},p_{1};t)={\frac {\sin {[(1-t)\Omega }]}{\sin \Omega }}p_{0}+{\frac {\sin[t\Omega ]}{\sin \Omega }}p_{1}.}$$ 
+
 The implementation of SLERP involves the following steps:
 - Normalize the input vectors to unit length, ensuring they signify directions rather than magnitudes.
 - Calculate the angle between these vectors using their dot product.