Update version.py (#1103)

* Update version.py

* Update README.md

README.md

@@ -9,7 +9,7 @@
 </p>
 
 ## News
-* 01/19/2025 [1.7.1](https://github.com/ModelCloud/GPTQModel/releases/tag/v1.7.1): Effective BPW (bits per weight) will now be logged during `load()`. Reduce loading time on Intel Arc A770/B580 `XPU` by 3.3x. Reduce memory usage in MLX conversion and fix Marlin kernel auto-select not checking CUDA compute version. 
+* 01/19/2025 [1.7.2](https://github.com/ModelCloud/GPTQModel/releases/tag/v1.7.2): Effective BPW (bits per weight) will now be logged during `load()`. Reduce loading time on Intel Arc A770/B580 `XPU` by 3.3x. Reduce memory usage in MLX conversion and fix Marlin kernel auto-select not checking CUDA compute version. 
 * 01/17/2025 [1.7.0](https://github.com/ModelCloud/GPTQModel/releases/tag/v1.7.0): 👀 ✨ `backend.MLX` added for runtime-conversion and execution of GPTQ models on Apple's `MLX` framework on Apple Silicon (M1+). Exports of `gptq` models to `mlx` also now possible. We have added `mlx` exported models to [huggingface.co/ModelCloud](https://huggingface.co/collections/ModelCloud/vortex-673743382af0a52b2a8b9fe2). ✨ `lm_head` quantization now fully support by GPTQModel without external pkg dependency. 
 * 01/07/2025 [1.6.1](https://github.com/ModelCloud/GPTQModel/releases/tag/v1.6.1): 🎉 New OpenAI api compatible end-point via `model.serve(host, port)`. Auto-enable flash-attention2 for inference.  Fixed `sym=False` loading regression. 
 * 01/06/2025 [1.6.0](https://github.com/ModelCloud/GPTQModel/releases/tag/v1.6.0): ⚡25% faster quantization. 35% reduction in vram usage vs v1.5. 👀 AMD ROCm (6.2+) support added and validated for 7900XT+ GPU. Auto-tokenizer loader via `load()` api. For most models you no longer need to manually init a tokenizer for both inference and quantization.

gptqmodel/version.py

@@ -13,4 +13,4 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-__version__ = "1.7.1-dev"
+__version__ = "1.7.2"