prep for 1.7.4 release (#1166)

* prep for 1.7.4 release

* Update version.py

* Update README.md

* Update README.md

Author: Qubitium

README.md

@@ -9,7 +9,7 @@
 </p>
 
 ## News
-* 01/22/2025 [1.7.4-dev]: New `compile()` api for ~4-8% inference tps improvement. Faster `pack()` for post-quantiztion model save. `Triton` kernel validated for Intel/`XPU` when Intel Triton packages are installed. Pending DeepSeek V3 model support. 
+* 01/26/2025 [1.7.4](https://github.com/ModelCloud/GPTQModel/releases/tag/v1.7.4): New `compile()` api for ~4-8% inference tps improvement. Faster `pack()` for post-quantiztion model save. `Triton` kernel validated for Intel/`XPU` when Intel Triton packages are installed. Fixed Transformers (bug) downcasting tokenizer class on save. 
 * 01/20/2025 [1.7.3](https://github.com/ModelCloud/GPTQModel/releases/tag/v1.7.3): New Telechat2 (China Telecom) and PhiMoE model support. Fixed `lm_head` weights duplicated in post-quantize save() for models with tied-embedding. 
 * 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. 

gptqmodel/version.py

@@ -13,4 +13,4 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-__version__ = "1.7.4-dev"
+__version__ = "1.7.4"