fix: pin padding_free=False to keep max_length enforced (trl 1.6+)

Newer Unsloth versions auto-enable SFTConfig's padding_free when it's
left unset, which conflicts with an explicit max_length + packing=False
and raises a ValueError at SFTTrainer init. Verified end-to-end on a
GTX 1650 (4GB VRAM): 60 steps complete cleanly, peak reserved memory
1.543 GB (42% of total), train_loss 1.662 -> 1.264.

examples/train_4gb_vram.py

@@ -94,6 +94,8 @@ def main():
         max_length                  = max_seq_length,
         dataset_num_proc            = 2,
         packing                     = False,  # True can spike VRAM on variable-length samples
+        padding_free                = False,  # Unsloth auto-enables this when unset, which conflicts
+                                               # with an explicit max_length + packing=False (trl 1.6+)
     )
 
     # ── 5. Initialize trainer ─────────────────────────────────────────────────