refactor: 改用递归子模块 init 替代统一 normal_(0.006)

- Embedding.reset_parameters: normal_(std=0.02)
- Linear.reset_parameters: kaiming_uniform_ + uniform_ bias
- Transformer._init_weights 通过 apply 递归调用子模块 reset_parameters
- 移除全局 normal_(0.006) 覆盖，各模块使用更合适的分布

astrai/model/components/embedding.py

@@ -9,5 +9,8 @@ class Embedding(nn.Module):
         super().__init__()
         self.weight = nn.Parameter(torch.empty((vocab_size, embedding_dim)))
 
+    def reset_parameters(self):
+        nn.init.normal_(self.weight, mean=0.0, std=0.02)
+
     def forward(self, x: Tensor) -> Tensor:
         return F.embedding(x, self.weight)