Fix label leakage: temporal split — use first 70% of events as input, predict purchase in last 30%. Remove n_purchases/purchase_rate from features.

Fix model loading: use from_pretrained() instead of torch.load() for safetensors format

Add 03_ecommerce_finetune.ipynb — next-purchase prediction with JointFusion, LightGBM baseline comparison

Update 02_ecommerce notebook: add HF login, memory-free cell, subsample option for <64GB RAM machines

Add 02_ecommerce_pretrain.ipynb — REES46 e-commerce pre-training with sequential entropy check, wandb, push to hub

Fix notebook: total_mem → total_memory, add hub_model_id push, add wandb logging support

Add 01_finance_pretrain.ipynb — Phase 3.1 notebook for pre-training on 5M Nigerian financial transactions