diff --git a/mamba_ssm/ops/selective_scan_interface.py b/mamba_ssm/ops/selective_scan_interface.py
index a41f1359..6f99b323 100644
--- a/mamba_ssm/ops/selective_scan_interface.py
+++ b/mamba_ssm/ops/selective_scan_interface.py
@@ -111,6 +111,25 @@ def selective_scan_fn(u, delta, A, B, C, D=None, z=None, delta_bias=None, delta_
     """
     return SelectiveScanFn.apply(u, delta, A, B, C, D, z, delta_bias, delta_softplus, return_last_state)
 
+def select_scan_fn_init_hidden(u, delta, A, B, C, D=None, z=None, delta_bias=None, delta_softplus=False,
+                               return_last_state=False, init_state=None):
+    """
+    Selective Scan with hidden state initialization
+    It uses the base kernel method but applies a transformation to B to mimic the initialization of the hidden state.
+    Memory and time overhead is minimal compared to ref method.
+    """
+    delta2 = delta + delta_bias[..., None].float()
+    v = F.softplus(delta2[:,:,0]) * u[:,:,0] + 1e-7
+    B = B.clone()
+    sig = (init_state[:,:,:] * torch.exp(F.softplus(delta2[:,:,0]).unsqueeze(-1) * A.unsqueeze(0)) ) / v.unsqueeze(-1)
+    dim = A.shape[0]
+    B = repeat(B, "B G N L -> B (G H) N L", H=dim // B.shape[1])
+    B = B.clone()
+    B[:,:,:,0] = B[:,:,:,0] + sig
+    C = C.clone()
+    C = repeat(C, "B G N L -> B (G H) N L", H=dim // C.shape[1])
+
+    return SelectiveScanFn.apply(u, delta, A, B, C, D, z, delta_bias, delta_softplus, return_last_state)
 
 def selective_scan_ref(u, delta, A, B, C, D=None, z=None, delta_bias=None, delta_softplus=False,
                       return_last_state=False):