model: add KORMoForCausalLM

Author: HelloKS

convert_hf_to_gguf.py

@@ -2370,7 +2370,8 @@ def prepare_tensors(self):
     "VLlama3ForCausalLM",
     "LlavaForConditionalGeneration",
     "VoxtralForConditionalGeneration",
-    "LlamaModel")
+    "LlamaModel",
+    "KORMoForCausalLM")
 class LlamaModel(TextModel):
     model_arch = gguf.MODEL_ARCH.LLAMA
     undo_permute = True
@@ -8237,7 +8238,6 @@ def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iter
 
         return [(self.map_tensor_name(name), data_torch)]
 
-
 @ModelBase.register("ExaoneForCausalLM")
 class ExaoneModel(TextModel):
     model_arch = gguf.MODEL_ARCH.EXAONE

gguf-py/gguf/tensor_mapping.py

@@ -154,7 +154,8 @@ class TensorNameMap:
             "model.layers.{bid}.operator_norm",                     # lfm2
             "model.transformer.blocks.{bid}.attn_norm",             # llada
             "layers.{bid}.input_layernorm",                         # qwen3-embedding
-            "model.layers.{bid}.attention_layernorm"                # apertus
+            "model.layers.{bid}.attention_layernorm",               # apertus
+            "model.layers.{bid}.pre_attention_layernorm",           # kormo
         ),
 
         # Attention norm 2
@@ -342,6 +343,7 @@ class TensorNameMap:
             "model.transformer.blocks.{bid}.ff_norm",                        # llada
             "layers.{bid}.post_attention_layernorm",                         # qwen3-embedding
             "model.layers.{bid}.feedforward_layernorm",                      # apertus
+            "model.layers.{bid}.pre_mlp_layernorm",                          # kormo
         ),
 
         # Pre feed-forward norm