| license: apache-2.0 | |
| base_model: Qwen/Qwen3.5-0.8B | |
| library_name: transformers | |
| tags: | |
| - qwen3.5 | |
| - unsloth | |
| - qat | |
| - edge | |
| - sft | |
| - int8-int4 | |
| # Cortex A 0.5 | |
| General-purpose **edge** checkpoint: Qwen3.5-0.8B full SFT with Unsloth | |
| **int8-int4 QAT** (4-bit weights + 8-bit dynamic activations). Target inference | |
| footprint ≈ **450MB including the vision tower**. | |
| This repo stores: | |
| - `checkpoint-*` — resumable Trainer states (optimizer + fake-quant QAT model) | |
| - `training/live_metrics.json` — loss, MTP loss, ppl, val loss/ppl, tok/s, grad norm, lr | |
| - `training/RESUME_POINTER.json` — last step for the next 12h Kaggle session | |
| - `qat_converted/` — real 4-bit TorchAO export (only after a completed epoch run) | |
| Training hardware: Kaggle **2× Tesla T4**, hard stop **11.5h**, DDP via `torchrun`. | |
| QAT scheme: **`int8-int4`**. | |