Update README.md (#2244)

Author: Qubitium

README.md

@@ -17,6 +17,7 @@
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 ## Latest News
+* 12/9/2025 [5.6.0](https://github.com/ModelCloud/GPTQModel/releases/tag/v5.6.0): ✨New `HF Kernel` for CPU optimized for `AMX`, `AVX2` and `AVX512`. Auto module tree for auto-model support. Added Afmoe and Dosts1 model support. Fixed pre-layer pass quantization speed regression. Imprpved HF Transformers, Peft and Optimum support for both GPTQ and AWQ. Fixed many AWQ compat bugs and regressions. 
 * 11/9/2025 [5.4.0](https://github.com/ModelCloud/GPTQModel/releases/tag/v5.4.0): ✨New Intel CPU and XPU hw optimized AWQ `TorchFusedAWQ` kernel. Torch Fused kernels now compatible with `torch.compile`. Fixed AWQ MoE model compatibility and reduced vram usage.
 * 11/3/2025 [5.2.0](https://github.com/ModelCloud/GPTQModel/releases/tag/v5.2.0): 🎉Minimax M2 support with [ModelCloud BF16 M2 Model](https://huggingface.co/ModelCloud/MiniMax-M2-BF16). New `VramStrategy.Balanced` quantization property for reduced memory usage for large MoE on multi-3090 (24GB) devices. ✨Marin model. New AWQ Torch reference kernel. Fix AWQ Marlin kernel for bf16. Fix GLM 4.5/4.6 MoE missing `mtp` layers on model save (HF bug). Modular refractor.  🎉AWQ support out of beta with full feature support in including multi-gpu quant and MoE vram saving.  ✨Brumby (attention free) model support. ✨Brumby (attention free) model support. ✨IBM Granite Nano support. New `calibration_concat_separator` config option.
 * 10/24/2025 [5.0.0](https://github.com/ModelCloud/GPTQModel/releases/tag/v5.0.0): 🎉 Data-parallel quant support for `MoE` models on multi-gpu using `nogil` Python. `offload_to_disk` support enabled by