# Attention scores between all word pairs
attention_scores = torch.mm(Q, K.transpose(0, 1))  # [10, 10] matrix
attention_weights = F.softmax(attention_scores, dim=1)  # Each row sums to 1

# Row i, column j = how much word i attends to word j