diff --git a/utils/das.py b/utils/das.py
index 2551715..9938076 100644
--- a/utils/das.py
+++ b/utils/das.py
@@ -71,7 +71,7 @@ def hook_fn_base(
     resid: Float[Tensor, "batch pos d_model"],
     hook: HookPoint,
     layer: int,
-    position: Optional[Int[Tensor, "batch"]],
+    position: Optional[Union[int, Int[Tensor, "batch"]]],
     new_value: Float[Tensor, "batch *pos d_model"]
 ):
     batch_size, seq_len, d_model = resid.shape
@@ -81,6 +81,13 @@ def hook_fn_base(
     if position is None:
         assert new_value.shape == resid.shape
         return new_value
+    if isinstance(position, int):
+        position = torch.tensor(position, device=resid.device)
+        position = einops.repeat(
+            position,
+            " -> batch",
+            batch=batch_size,
+        )
     new_value_repeat = einops.repeat(
         new_value,
         "batch d_model -> batch pos d_model",
diff --git a/utils/prompts.py b/utils/prompts.py
index 8f035f5..3e4ac81 100644
--- a/utils/prompts.py
+++ b/utils/prompts.py
@@ -512,9 +512,12 @@ def __init__(
             prompt_type is not None and len(prompt_type.get_placeholders()) == 0
         )
         if position is None and no_placeholders:
-            mask = get_attention_mask(
-                tokenizer, clean_tokens, prepend_bos=False
-            )
+            if tokenizer is None:
+                mask = torch.ones_like(clean_tokens, dtype=torch.bool)
+            else:
+                mask = get_attention_mask(
+                    tokenizer, clean_tokens, prepend_bos=False
+                )
             position = get_final_non_pad_token(mask)
         elif position is None and prompt_type is not None:
             # Default to first placeholder position