diff --git a/miniseries.sh b/miniseries.sh
index 077418a..0a6947e 100644
--- a/miniseries.sh
+++ b/miniseries.sh
@@ -1,29 +1,39 @@
 #!/bin/bash
 
 # See speedrun.sh for more comments
+# Usage: ./miniseries.sh [series_name]
+# Example: ./miniseries.sh jan11
+# Default series name is today's date (e.g., jan11)
 
 export OMP_NUM_THREADS=1
 export NANOCHAT_BASE_DIR="$HOME/.cache/nanochat"
 mkdir -p $NANOCHAT_BASE_DIR
 
-# uv
-command -v uv &> /dev/null || curl -LsSf https://astral.sh/uv/install.sh | sh
-[ -d ".venv" ] || uv venv
-uv sync --extra gpu
-source .venv/bin/activate
+# Setup (skip with SKIP_SETUP=1)
+if [ -z "$SKIP_SETUP" ]; then
+    # uv
+    command -v uv &> /dev/null || curl -LsSf https://astral.sh/uv/install.sh | sh
+    [ -d ".venv" ] || uv venv
+    uv sync --extra gpu
+    source .venv/bin/activate
 
-# Tokenizer
-python -m nanochat.dataset -n 240
-python -m scripts.tok_train --max_chars=2000000000 --vocab_size=32768
+    # Tokenizer
+    python -m nanochat.dataset -n 240
+    python -m scripts.tok_train --max_chars=2000000000 --vocab_size=32768
+else
+    source .venv/bin/activate
+fi
 
+# Series name: from arg, env var, or default to today's date (e.g., jan11)
+SERIES_NAME="${1:-${SERIES_NAME:-$(date +%b%d | tr '[:upper:]' '[:lower:]')}}"
 # Depths to train (the "miniseries")
 DEPTHS=(10 11 12 13 14 15 16 17 18 19 20)
 # Hardware
 NPROC_PER_NODE="${NPROC_PER_NODE:-8}"
 # Logging
-WANDB_RUN="${WANDB_RUN:-jan7_miniseries}"
+WANDB_RUN="${WANDB_RUN:-${SERIES_NAME}_miniseries}"
 
-RESULTS_DIR="$NANOCHAT_BASE_DIR/jan7_miniseries_results"
+RESULTS_DIR="$NANOCHAT_BASE_DIR/${SERIES_NAME}_miniseries_results"
 mkdir -p "$RESULTS_DIR"
 RESULTS_FILE="$RESULTS_DIR/results.csv"
 
@@ -37,13 +47,13 @@ log() {
 }
 
 log "=============================================="
-log "Jan 7 Miniseries Training"
+log "${SERIES_NAME} Miniseries Training"
 log "=============================================="
 
 for d in "${DEPTHS[@]}"; do
     log "Training d=$d..."
 
-    TAG="jan7_miniseries_d${d}"
+    TAG="${SERIES_NAME}_miniseries_d${d}"
     START_TIME=$(date +%s)
 
     # Train the model with natural horizon (target_param_data_ratio default)
@@ -84,7 +94,7 @@ for d in "${DEPTHS[@]}"; do
 done
 
 log "=============================================="
-log "Jan 7 Miniseries Complete!"
+log "${SERIES_NAME} Miniseries Complete!"
 log "=============================================="
 log "Results saved to: $RESULTS_FILE"
 echo ""