diff --git a/lerobot/common/datasets/factory.py b/lerobot/common/datasets/factory.py
index 276dc761..4e02f704 100644
--- a/lerobot/common/datasets/factory.py
+++ b/lerobot/common/datasets/factory.py
@@ -86,13 +86,8 @@ def make_offline_buffer(
     else:
         raise ValueError(cfg.env.name)
 
-    # TODO(rcadene): backward compatiblity to load pretrained pusht policy
-    dataset_id = cfg.get("dataset_id")
-    if dataset_id is None and cfg.env.name == "pusht":
-        dataset_id = "pusht"
-
     offline_buffer = clsfunc(
-        dataset_id=dataset_id,
+        dataset_id=cfg.dataset_id,
         sampler=sampler,
         batch_size=batch_size,
         root=DATA_DIR,
diff --git a/lerobot/configs/policy/diffusion.yaml b/lerobot/configs/policy/diffusion.yaml
index acb368ed..4d6eedca 100644
--- a/lerobot/configs/policy/diffusion.yaml
+++ b/lerobot/configs/policy/diffusion.yaml
@@ -103,29 +103,3 @@ optimizer:
   betas: [0.95, 0.999]
   eps: 1.0e-8
   weight_decay: 1.0e-6
-
-training:
-  device: "cuda:0"
-  seed: 42
-  debug: False
-  resume: True
-  # optimization
-  # lr_scheduler: cosine
-  # lr_warmup_steps: 500
-  num_epochs: 8000
-  # gradient_accumulate_every: 1
-  # EMA destroys performance when used with BatchNorm
-  # replace BatchNorm with GroupNorm.
-  # use_ema: True
-  freeze_encoder: False
-  # training loop control
-  # in epochs
-  rollout_every: 50
-  checkpoint_every: 50
-  val_every: 1
-  sample_every: 5
-  # steps per epoch
-  max_train_steps: null
-  max_val_steps: null
-  # misc
-  tqdm_interval_sec: 1.0