fix kd test

src/axolotl/datasets.py

@@ -94,9 +94,15 @@ def wrap_dataset_for_tokenized_prompt(
         if prompt_tokenizer.supports_batched:
             map_kwargs["batched"] = True
 
-        # Peek at the first example to get original column names
-        first_example = next(iter(dataset))
-        original_columns = list(first_example.keys())
+        # For IterableDataset, we need to get original columns to remove them.
+        # We'll peek at the first example using a separate iterator to avoid consuming the main one.
+        def peek_and_get_columns():
+            # Create a fresh iterator just for peeking
+            temp_iter = iter(dataset)
+            first_example = next(temp_iter)
+            return list(first_example.keys())
+
+        original_columns = peek_and_get_columns()
 
         # Map the dataset and remove original columns
         # This ensures only tokenized columns remain

src/axolotl/utils/trainer.py

@@ -471,8 +471,13 @@ def calculate_total_num_steps(cfg, train_dataset, update=True):
                 mp_start_method=cfg.sample_packing_mp_start_method or "fork",
             )
 
+            # Remove length column only if it exists
+            dataset_for_loader = train_dataset
+            if "length" in train_dataset.column_names:
+                dataset_for_loader = train_dataset.remove_columns(["length"])
+
             data_loader = DataLoader(
-                train_dataset.remove_columns(["length"]),
+                dataset_for_loader,
                 batch_sampler=sampler,
             )
             data_loader_len = len(data_loader) * cfg.micro_batch_size // cfg.batch_size

tests/e2e/integrations/test_kd.py

@@ -25,7 +25,7 @@ def min_cfg(temp_dir):
         "liger_rms_norm": True,
         "liger_glu_activation": True,
         "torch_compile": True,
-        "chat_template": "llama3",
+        "chat_template": "qwen3",
         "kd_trainer": True,
         "kd_ce_alpha": 0.1,
         "kd_alpha": 0.9,