quantize linear

lora/convert.py

@@ -28,8 +28,6 @@ def quantize(weights, config, args):
         model,
         args.q_group_size,
         args.q_bits,
-        linear_class_predicate=lambda m: isinstance(m, nn.Linear)
-        and m.weight.shape[0] != config["vocab_size"],
     )
 
     # Update the config:

lora/lora.py

@@ -339,9 +339,6 @@ def load_model(folder: str):
         model_args = ModelArgs(**config)
     model = Model(model_args)
     if quantization is not None:
-        quantization["linear_class_predicate"] = lambda m: isinstance(
-            m, nn.Linear
-        ) and (m.weight.shape[0] != model_args.vocab_size)
         nn.QuantizedLinear.quantize_module(model, **quantization)
 
     weights = mx.load(str(model_path / "weights.npz"))