| library_name: pytorch | |
| base_model: microsoft/FrogBoss-32B-2510 | |
| tags: | |
| - quantized | |
| - custom-code | |
| - safetensors | |
| # Mixed STQ / FP8 checkpoint | |
| Source: `microsoft/FrogBoss-32B-2510` | |
| Source revision: `cc930952b8751de86a2a44debaf26e45e677a291` | |
| MLP projections use custom Sherry-style STQ: | |
| 42 bytes per 256 weights, with unit importance weights. | |
| Attention projections, embeddings, and the output head use scaled E4M3FN | |
| FP8 with FP32 per-row scales. Vectors and scalars use FP16. | |
| Packed checkpoint size: 11.731 GB. | |
| This is NOT a verified Tencent serialization format. It requires the | |
| matching mixed-stq-fp8-v2 Colab loader and cannot be loaded through ordinary | |
| Transformers `from_pretrained()`. | |
| No activation calibration, recovery training, or quality evaluation has | |
| been performed. Meaningful generation and useful accuracy are not | |
| guaranteed. | |
| Repository naming does not change the source model's parameter count. | |
| Retain the accompanying Colab notebook as the custom runtime. | |
| Review the source model's license before redistribution. | |