WandB API Key Length Fix | Generated by AI

Home 2026.06

Question: In the nanochat training script, how does the tracker=wandb parameter work, and why is WandB complaining that the API key format is not 48 characters?

Answer:

The tracker=wandb argument tells the training script to log metrics, gradients, and samples to Weights & Biases. WandB’s complaint about key length suggests you’re either using an old API key format or an outdated WandB version.

How it works

The script likely initializes WandB early in scripts/base_train.py:

if config.tracker == "wandb":
    import wandb
    wandb.init(project="nanochat", config=config)

WandB reads your API key from (in order of precedence):

  1. WANDB_API_KEY environment variable
  2. ~/.netrc file (from wandb login)
  3. .wandb local directory

The 48-char issue

WandB changed API key format around mid-2024:

If WandB is complaining about 48 chars, it expects the new format, meaning your old key is invalid.

Fix it (3 steps)

Step 1: Regenerate your key

# Log out of old session
wandb logout

# Login again (opens browser, generates new key)
wandb login

Paste your new key from https://wandb.ai/authorize (should be 48 chars, starting with wab_).

Step 2: Verify it’s saved

cat ~/.netrc | grep wandb
# Should show something like: password wab_xxxxxxxxxxxxxxxxxxxxx

Step 3: Or set via env variable

export WANDB_API_KEY="wab_xxxxxxxxxxxxxxxxxxxxx"

# Then run training
cd /mnt/data/nanochat && PYTORCH_ALLOC_CONF=expandable_segments:True .venv/bin/python -m scripts.base_train \
  --run=rtx4070-d12-200k \
  --tracker=wandb \
  ...

Alternative: Skip WandB if you just want training

If WandB is slowing you down or adding friction, use --tracker=none or comment it out:

# ... --tracker=none ...

Then monitor loss locally via tensorboard, raw logs, or parse the training output.

Pro tip: For long runs like 200k iterations, WandB is worth it (checkpoints your run, lets you track across machine restarts). But make sure your key is current — regenerate once and you’re good.

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