# fix for SmolVLM2, missing `num_attention_heads` in config.json
if self.hf_arch == "VLlama3ForCausalLM":
self.hparams["num_attention_heads"] = self.hparams.get("num_attention_heads", 32)
- hparams = ModelBase.load_hparams(self.dir_model, is_mistral_format=False)
- self.origin_hf_arch = hparams.get('architectures', [None])[0]
+ # Mistral consolidated format has no config.json; origin_hf_arch is HF-only.
+ if self.is_mistral_format:
+ self.origin_hf_arch = None
+ else:
+ hparams = ModelBase.load_hparams(self.dir_model, is_mistral_format=False)
+ self.origin_hf_arch = hparams.get('architectures', [None])[0]
def set_vocab(self):
if self.origin_hf_arch == "GlmasrModel":
self.gguf_writer.add_vision_use_silu(True)
# spatial_merge_size
- if self.find_vparam(["mm_projector_id"]) == "patch_merge":
+ if self.find_vparam(["mm_projector_id"], optional=True) == "patch_merge":
self.gguf_writer.add_vision_spatial_merge_size(
self.find_vparam(["spatial_merge_size"])
)
def map_tensor_name(self, name: str, try_suffixes: Sequence[str] = (".weight", ".bias")) -> str:
if name == "vision_language_adapter.w_in.weight":
return "mm.1.weight"
+ elif name == "vision_language_adapter.w_in.bias":
+ return "mm.1.bias"
elif name == "vision_language_adapter.w_out.weight":
return "mm.2.weight"
+ elif name == "vision_language_adapter.w_out.bias":
+ return "mm.2.bias"
return super().map_tensor_name(name, try_suffixes)