Feat 22103. Update to resolve review comments #2

Author: samuraieng

convert_hf_to_gguf.py

@@ -13197,6 +13197,28 @@ def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iter
             yield from super().modify_tensors(data_torch, name, bid)
 
 
+@ModelBase.register("Sarashina2VisionForCausalLM")
+class Sarashina2VLTextModel(LlamaModel):
+    model_arch = gguf.MODEL_ARCH.LLAMA
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        hparams = ModelBase.load_hparams(self.dir_model, is_mistral_format=False)
+        self.origin_hf_arch = hparams.get('architectures', [None])[0]
+
+    def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None):
+        if name.startswith("llm."):
+            name = name[len("llm."):]
+            yield from super().modify_tensors(data_torch, name, bid)
+
+
+@ModelBase.register("Sarashina2VisionForCausalLM")
+class Sarashina2VLVisionModel(Qwen2VLVisionModel):
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.global_config['model_type'] = "qwen2_vl"
+
+
 ###### CONVERSION LOGIC ######
 
 
@@ -13454,6 +13476,8 @@ def get_model_architecture(hparams: dict[str, Any], model_type: ModelType) -> st
     # TODO: refactor this later to avoid adding exception here
     if model_type == ModelType.TEXT and arch == "StepVLForConditionalGeneration":
         return arch
+    if model_type == ModelType.TEXT and arch == "Sarashina2VisionForCausalLM":
+        return "Sarashina2VisionForCausalLM"
 
     # if "architectures" is found in the sub-config, use that instead
     if model_type == ModelType.TEXT and text_config.get("architectures") is not None: