prepare for v4.2.5 maint release (#1803)

* prepare for v4.2.5 maint release

* Update README.md

Author: Qubitium

README.md

@@ -17,7 +17,8 @@
 </p>
 
 ## Latest News
-* 09/12/2025 [4.2.0](https://github.com/ModelCloud/GPTQModel/releases/tag/v4.1.0): ✨ New Models Support: Qwen3-Next, Apertus, Kimi K2, Klear, FastLLM, Nemotron H. New `fail_safe` `boolean` toggle to `.quantize()` to patch-fix non-activated `MoE` modules due to highly uneven MoE model training. Fixed LavaQwen2 compat. Patch fix GIL=0 cuda error for multi-gpu. Fix compat with autoround + new transformers. 
+* 09/16/2025 [4.2.5](https://github.com/ModelCloud/GPTQModel/releases/tag/v4.2.5): `hyb_act` renamed to `act_group_aware`. Removed finicky `torch` import within `setup.py`. Packing bug fix and prebuilt Pytorch 2.8 whls. 
+* 09/12/2025 [4.2.0](https://github.com/ModelCloud/GPTQModel/releases/tag/v4.2.0): ✨ New Models Support: Qwen3-Next, Apertus, Kimi K2, Klear, FastLLM, Nemotron H. New `fail_safe` `boolean` toggle to `.quantize()` to patch-fix non-activated `MoE` modules due to highly uneven MoE model training. Fixed LavaQwen2 compat. Patch fix GIL=0 cuda error for multi-gpu. Fix compat with autoround + new transformers. 
 * 09/04/2025 [4.1.0](https://github.com/ModelCloud/GPTQModel/releases/tag/v4.1.0): ✨ Meituan LongCat Flash Chat, Llama 4, GPT-OSS (BF16), and GLM-4.5-Air support.  New experiemental `mock_quantization` config to skip complex computational code paths during quantization to accelerate model quant testing. 
 * 08/21/2025 [4.0.0](https://github.com/ModelCloud/GPTQModel/releases/tag/v4.0.0): 🎉 New Group Aware Reordering (GAR) support. New models support: Bytedance Seed-OSS, Baidu Ernie, Huawei PanGu, Gemma3, Xiaomi Mimo, Qwen 3/MoE, Falcon H1, GPT-Neo. Memory leak and multiple model compatibility fixes related to Transformers >= 4.54. Python >= 3.13t free-threading support added with near N x GPU linear scaling for quantization of MoE models and also linear N x Cpu Core scaling of packing stage. Early access Pytorch 2.8 fused-ops on Intel XPU for up to 50% speedup.
 * 08/19/2025 4.0.0-dev `main`: Fix quantization memory usage due to some model's incorrect application of `config.use_cache` during inference. Fixed `Transformers` >= 4.54.0 compat which changed layer forward return signature for some models. 

gptqmodel/version.py

@@ -14,4 +14,4 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-__version__ = "4.3.0-dev"
+__version__ = "4.2.5"