| license: mit | |
| tags: | |
| - sparseflow | |
| - sparse-attention | |
| - conversational | |
| - efficient | |
| # SparseFlow-Chat v5 | |
| An efficient conversational AI with **sparse attention** - achieving significant compute savings. | |
| ## 🚀 Performance | |
| | Metric | Value | | |
| |--------|-------| | |
| | Parameters | 39,840,002 | | |
| | Perplexity | 1.00 | | |
| | Token Sparsity | 87.5% | | |
| | Attention Saved | 87.5% | | |
| ## 🏗️ Architecture | |
| - **Sparse Token Router**: O(n×k) instead of O(n²) attention | |
| - **Persistent Memory Banks**: Store and retrieve knowledge | |
| - **Channel Sparsity**: Activates only top-k channels | |
| ### Complexity Comparison | |
| | Operation | Transformer | SparseFlow | Speedup | | |
| |-----------|-------------|------------|--------| | |
| | Attention | O(n²) | O(n×k) | 8x | | |
| | FFN | O(n×d²) | O(n×k×d) | ~4x | | |
| ## 💬 Usage | |
| ```python | |
| # Load model | |
| import torch | |
| checkpoint = torch.load("model.pt") | |
| # ... initialize model with config.json | |
| model.load_state_dict(checkpoint['model']) | |
| # Chat | |
| response = chat("What is the capital of France?") | |
| # -> "The capital of France is Paris." | |
| ``` | |
| ## 📝 Created By | |
| **Logo (Mike Amega)** — [Ame Web Studio](https://github.com/AmeWebStudio) | |
| February 2025 | |