--- license: other license_name: personal-use-free-commercial-paid license_link: LICENSE tags: - onnx - smartwatch - intent-classification - text-generation - wearable library_name: onnxruntime pipeline_tag: text-generation --- # Smartwatch LM v0.2 Exported from [collab-run-2](../collab-run-2) training. Small GPT for wrist-wearable chat with intent tags like ``. ## Model details | Property | Value | |----------|-------| | Architecture | 6-layer causal GPT (**~15.4M params**) | | Context length | 256 tokens | | Vocab size | 5533 (BPE) | | Best val loss | 0.3243 | | Training data | tinydata.txt, deepdata.txt, tinydata1.txt, data1.txt, data3.txt | | Export version | 0.2 | ## Files | File | Purpose | |------|---------| | `smartwatch_lm_merged.onnx` | On-device inference (ONNX Runtime, opset 17, ~0 MB) | | `checkpoint.pt` | PyTorch weights | | `tokenizer.json` | BPE tokenizer | | `config.json` | Architecture + ONNX I/O | | `model.py` / `chat.py` | PyTorch load + REPL | | `reply_utils.py` | BPE cleanup, intent parse, slot fill | | `onnx_sample.py` | ONNX generate sample | ## Quick start ```bash pip install numpy onnxruntime tokenizers python onnx_sample.py "How many steps today?" ``` ```bash pip install torch tokenizers python chat.py ``` ## ONNX I/O - **Input:** `input_ids` int64 `[batch, seq]` (max seq = 256) - **Output:** `logits` float `[batch, seq, vocab_size]` See [Export-0.1 docs](docs/) for gibberish cleanup, intents, and device integration. ## License **Personal use is free.** You may use, modify, and share this model for non-commercial, personal, educational, and research purposes under the terms in [LICENSE](LICENSE). **Commercial use requires a paid license.** If you want to use this model in a product, service, or other commercial context, contact the repository maintainer to obtain commercial licensing terms.