diff --git a/bin/predict.py b/bin/predict.py
index def13b88f..79ec5ab35 100644
--- a/bin/predict.py
+++ b/bin/predict.py
@@ -240,6 +240,7 @@ def main(
     epoch: int = typer.Option(...),
     batch_size: int = None,
     num_samples: int = 3,
+    input_transform_dataset: str = None,
     input_transform_key: str = None,
     ensemble_member: str = DEFAULT_ENSEMBLE_MEMBER,
 ):
@@ -247,6 +248,10 @@ def main(
     config = load_config(config_path)
     if batch_size is not None:
         config.eval.batch_size = batch_size
+    if input_transform_dataset is not None:
+        config.data.input_transform_dataset = input_transform_dataset
+    else:
+        config.data.input_transform_dataset = dataset
     if input_transform_key is not None:
         config.data.input_transform_key = input_transform_key
 
@@ -254,7 +259,7 @@ def main(
         workdir=workdir,
         checkpoint=f"epoch-{epoch}",
         dataset=dataset,
-        input_xfm=config.data.input_transform_key,
+        input_xfm=f"{config.data.input_transform_dataset}-{config.data.input_transform_key}",
         split=split,
         ensemble_member=ensemble_member,
     )
@@ -270,6 +275,7 @@ def main(
     eval_dl, _, target_transform = get_dataloader(
         dataset,
         config.data.dataset_name,
+        config.data.input_transform_dataset,
         config.data.input_transform_key,
         config.data.target_transform_key,
         transform_dir,
diff --git a/src/ml_downscaling_emulator/bin/evaluate.py b/src/ml_downscaling_emulator/bin/evaluate.py
index e6f78f36e..5915002cc 100644
--- a/src/ml_downscaling_emulator/bin/evaluate.py
+++ b/src/ml_downscaling_emulator/bin/evaluate.py
@@ -61,6 +61,7 @@ def sample(
     epoch: int = typer.Option(...),
     batch_size: int = None,
     num_samples: int = 1,
+    input_transform_dataset: str = None,
     input_transform_key: str = None,
     ensemble_member: str = DEFAULT_ENSEMBLE_MEMBER,
 ):
@@ -70,6 +71,10 @@ def sample(
 
     if batch_size is not None:
         config.eval.batch_size = batch_size
+    if input_transform_dataset is not None:
+        config.data.input_transform_dataset = input_transform_dataset
+    else:
+        config.data.input_transform_dataset = dataset
     if input_transform_key is not None:
         config.data.input_transform_key = input_transform_key
 
@@ -77,7 +82,7 @@ def sample(
         workdir=workdir,
         checkpoint=f"epoch-{epoch}",
         dataset=dataset,
-        input_xfm=config.data.input_transform_key,
+        input_xfm=f"{config.data.input_transform_dataset}-{config.data.input_transform_key}",
         split=split,
         ensemble_member=ensemble_member,
     )
@@ -88,6 +93,7 @@ def sample(
     eval_dl, _, target_transform = get_dataloader(
         dataset,
         config.data.dataset_name,
+        config.data.input_transform_dataset,
         config.data.input_transform_key,
         config.data.target_transform_key,
         transform_dir,
diff --git a/src/ml_downscaling_emulator/deterministic/run_lib.py b/src/ml_downscaling_emulator/deterministic/run_lib.py
index 407444cd8..79af70e34 100644
--- a/src/ml_downscaling_emulator/deterministic/run_lib.py
+++ b/src/ml_downscaling_emulator/deterministic/run_lib.py
@@ -77,6 +77,7 @@ def train(config, workdir):
 
     # Build dataloaders
     train_dl, _, _ = get_dataloader(
+        config.data.dataset_name,
         config.data.dataset_name,
         config.data.dataset_name,
         config.data.input_transform_key,
@@ -89,6 +90,7 @@ def train(config, workdir):
         evaluation=False,
     )
     val_dl, _, _ = get_dataloader(
+        config.data.dataset_name,
         config.data.dataset_name,
         config.data.dataset_name,
         config.data.input_transform_key,
diff --git a/src/ml_downscaling_emulator/score_sde_pytorch_hja22/run_lib.py b/src/ml_downscaling_emulator/score_sde_pytorch_hja22/run_lib.py
index b51672bd5..f82cd76ee 100644
--- a/src/ml_downscaling_emulator/score_sde_pytorch_hja22/run_lib.py
+++ b/src/ml_downscaling_emulator/score_sde_pytorch_hja22/run_lib.py
@@ -110,8 +110,8 @@ def train(config, workdir):
     ) as (wandb_run, writer):
     # Build dataloaders
     dataset_meta = DatasetMetadata(config.data.dataset_name)
-    train_dl, _, _ = get_dataloader(config.data.dataset_name, config.data.dataset_name, config.data.input_transform_key, config.data.target_transform_key, transform_dir, batch_size=config.training.batch_size, split="train", ensemble_members=dataset_meta.ensemble_members(), include_time_inputs=config.data.time_inputs, evaluation=False)
-    eval_dl, _, _ = get_dataloader(config.data.dataset_name, config.data.dataset_name, config.data.input_transform_key, config.data.target_transform_key, transform_dir, batch_size=config.training.batch_size, split="val", ensemble_members=dataset_meta.ensemble_members(), include_time_inputs=config.data.time_inputs, evaluation=False)
+    train_dl, _, _ = get_dataloader(config.data.dataset_name, config.data.dataset_name, config.data.dataset_name, config.data.input_transform_key, config.data.target_transform_key, transform_dir, batch_size=config.training.batch_size, split="train", ensemble_members=dataset_meta.ensemble_members(), include_time_inputs=config.data.time_inputs, evaluation=False)
+    eval_dl, _, _ = get_dataloader(config.data.dataset_name, config.data.dataset_name, config.data.dataset_name, config.data.input_transform_key, config.data.target_transform_key, transform_dir, batch_size=config.training.batch_size, split="val", ensemble_members=dataset_meta.ensemble_members(), include_time_inputs=config.data.time_inputs, evaluation=False)
 
     # Initialize model.
     score_model = mutils.create_model(config)
diff --git a/src/ml_downscaling_emulator/torch.py b/src/ml_downscaling_emulator/torch.py
index aa0b6a90b..857af654c 100644
--- a/src/ml_downscaling_emulator/torch.py
+++ b/src/ml_downscaling_emulator/torch.py
@@ -112,6 +112,7 @@ def custom_collate(batch):
 def get_dataloader(
     active_dataset_name,
     model_src_dataset_name,
+    input_transform_dataset_name,
     input_transform_key,
     target_transform_key,
     transform_dir,
@@ -127,6 +128,7 @@ def get_dataloader(
     Args:
       active_dataset_name: Name of dataset from which to load data splits
       model_src_dataset_name: Name of dataset used to train the diffusion model (may be the same)
+      input_transform_dataset_name: Name of dataset to use for fitting input transform (may be the same as active_dataset_name or model_src_dataset_name)
       transform_dir: Path to where transforms should be stored
       input_transform_key: Name of input transform pipeline to use
       target_transform_key: Name of target transform pipeline to use
@@ -140,6 +142,7 @@ def get_dataloader(
     xr_data, transform, target_transform = get_dataset(
         active_dataset_name,
         model_src_dataset_name,
+        input_transform_dataset_name,
         input_transform_key,
         target_transform_key,
         transform_dir,