v2: Updated notebook with real dataset training

v2: Updated README with Real Mamba SSM and real dataset info

v2: Training with real datasets, Mamba SSM, push-to-hub

v2: Real Mamba SSM backbone (pure PyTorch), fixes torch._utils error

v1.4: replace SSM scan with parallel causal linear attn, batch wavelet subbands, use F.scaled_dot_product_attention, fix AMP on CPU

v1.4: replace SSM scan with parallel causal linear attn, batch wavelet subbands, use F.scaled_dot_product_attention, fix AMP on CPU

v1.3: vectorized SSM scan, fix NaN, all 5 stage cells — ArtFlow_Training.ipynb

v1.3: vectorized SSM scan, fix NaN, all 5 stage cells — artflow_model.py

Update README for v1.2 — clean repo structure

Remove old scripts (superseded by artflow_train.py)

Rebuild notebook: imports from repo scripts, no code duplication

Add training script with modern APIs (no deprecations)

Update README with complete training notebook and stability mechanisms

Add standalone training stability test (100-step validation)

Add complete Colab-friendly training notebook with stability mechanisms

Add Stage 1 training script (Colab/Kaggle compatible)

Add validated PyTorch prototype implementation

Add complete architecture specification (1000+ lines)

Add ArtFlow architecture specification

initial commit