from gguf.constants import GGUFValueType
# reuse model definitions from the conversion/ package
-from conversion import LazyTorchTensor, ModelBase, get_model_class
+from conversion import LazyTorchTensor, ModelBase, get_model_class, ModelType, get_model_architecture
logger = logging.getLogger("lora-to-gguf")
hparams = ModelBase.load_hparams(dir_base_model, False)
with torch.inference_mode():
+ model_arch = get_model_architecture(hparams, ModelType.TEXT)
try:
- model_arch = hparams.get("text_config", {}).get("architectures", hparams["architectures"])[0]
- logger.info("Using model architecture: %s", model_arch)
model_class = get_model_class(model_arch)
+ logger.info("Using model architecture: %s", model_arch)
except NotImplementedError:
- logger.error(f"Model {hparams['architectures'][0]} is not supported")
+ logger.error(f"Model {model_arch} is not supported")
sys.exit(1)
class LoraModel(model_class): # ty: ignore[unsupported-base]