diff --git a/scripts/mid_train.py b/scripts/mid_train.py
index 6c2b82f..fa86f55 100644
--- a/scripts/mid_train.py
+++ b/scripts/mid_train.py
@@ -13,15 +13,17 @@ from collections import deque
 import os
 os.environ["PYTORCH_CUDA_ALLOC_CONF"] = "expandable_segments:True"
 import time
-import wandb
+
 import torch
+import torch.distributed as dist
+
 from contextlib import nullcontext
-from nanochat.common import compute_init, compute_cleanup, print0, DummyWandb, get_base_dir, autodetect_device_type
+from nanochat.common import compute_init, compute_cleanup, print0, get_wandb, get_base_dir, autodetect_device_type
 from nanochat.tokenizer import get_token_bytes
 from nanochat.checkpoint_manager import save_checkpoint
 from nanochat.loss_eval import evaluate_bpb
 from nanochat.checkpoint_manager import load_model
-import torch.distributed as dist
+
 
 from tasks.common import TaskMixture
 from tasks.gsm8k import GSM8K
@@ -62,8 +64,7 @@ synchronize = torch.cuda.synchronize if device_type == "cuda" else lambda: None
 get_max_memory = torch.cuda.max_memory_allocated if device_type == "cuda" else lambda: 0
 
 # wandb logging init
-use_dummy_wandb = run == "dummy" or not master_process
-wandb_run = DummyWandb() if use_dummy_wandb else wandb.init(project="nanochat-mid", name=run, config=user_config)
+wandb_run = get_wandb("nanochat-mid" , run=run, master_process=master_process, user_config=user_config)
 
 # Load the model and tokenizer
 model, tokenizer, meta = load_model("base", device, phase="train", model_tag=model_tag, step=step)