diff --git a/src/lm_saes/config.py b/src/lm_saes/config.py
index 75b50c3..8048346 100644
--- a/src/lm_saes/config.py
+++ b/src/lm_saes/config.py
@@ -394,6 +394,8 @@ def __post_init__(self):
             assert 0 <= self.lr_cool_down_steps <= 1.0
             self.lr_cool_down_steps = int(self.lr_cool_down_steps * total_training_steps)
             print_once(f"Learning rate cool down steps: {self.lr_cool_down_steps}")
+        if self.finetuning:
+            assert self.sae.l1_coefficient == 0.0, "L1 coefficient must be 0.0 for finetuning."
 
 @dataclass(kw_only=True)
 class LanguageModelSAEPruningConfig(LanguageModelSAERunnerConfig):
diff --git a/src/lm_saes/sae.py b/src/lm_saes/sae.py
index 1630057..1f011ab 100644
--- a/src/lm_saes/sae.py
+++ b/src/lm_saes/sae.py
@@ -140,12 +140,10 @@ def train_base_parameters(self):
             p.requires_grad_(True)
 
     def train_finetune_for_suppression_parameters(self):
-        """Set the parameters to be trained for feature suppression."""
+        """Set the parameters to be trained against feature suppression."""
+
+        finetune_for_suppression_parameters = [self.decoder.weight]
 
-        finetune_for_suppression_parameters = [
-            self.feature_act_scale,
-            self.decoder.weight,
-        ]
         if self.cfg.use_decoder_bias:
             finetune_for_suppression_parameters.append(self.decoder.bias)
         for p in self.parameters():
diff --git a/src/lm_saes/utils/huggingface.py b/src/lm_saes/utils/huggingface.py
index d51bae0..7807d4f 100644
--- a/src/lm_saes/utils/huggingface.py
+++ b/src/lm_saes/utils/huggingface.py
@@ -4,6 +4,7 @@
 import os
 import shutil
 from huggingface_hub import create_repo, upload_folder, snapshot_download
+from lm_saes.utils.misc import print_once
 
 
 def upload_pretrained_sae_to_hf(sae_path: str, repo_id: str, private: bool = False):
@@ -54,6 +55,7 @@ def parse_pretrained_name_or_path(pretrained_name_or_path: str):
     if os.path.exists(pretrained_name_or_path):
         return pretrained_name_or_path
     else:
+        print_once(f'Local path `{pretrained_name_or_path}` not found. Downloading from huggingface model hub.')
         repo_id = "/".join(pretrained_name_or_path.split("/")[:2])
         hook_point = "/".join(pretrained_name_or_path.split("/")[2:])
         return download_pretrained_sae_from_hf(repo_id, hook_point)
\ No newline at end of file