Unify the model type checking (#1905)

python/sglang/srt/models/llama.py

@@ -409,11 +409,13 @@ class LlamaForCausalLM(nn.Module):
         if (
             hasattr(self.config, "tie_word_embeddings")
             and self.config.tie_word_embeddings
+            and "lm_head.weight" in params_dict
         ):
             # Tie output embedding layer to input embedding layer, to solve issues where lm_head.weight is missing
             param = self.lm_head.weight
             weight_loader = getattr(param, "weight_loader", default_weight_loader)
             weight_loader(param, self.model.embed_tokens.weight)
+
         apply_torchao_config_(self, params_dict, set(["proj.weight"]))