update doc

Signed-off-by: zhenwei-intel <[email protected]>

Author: zhenwei-intel

docs/weightonlyquant.md

@@ -147,7 +147,7 @@ loaded_model = AutoModelForCausalLM.from_pretrained(saved_dir)
 > Note: For LLM runtime model loading usage, please refer to [neural_speed readme](https://github.com/intel/neural-speed/blob/main/README.md#quick-start-transformer-like-usage)
 
 ## Examples For Intel GPU
-Intel-extension-for-transformers implement weight-only quantization for intel GPU(PVC/ARC/MTL) with [Intel-extension-for-pytorch](https://github.com/intel/intel-extension-for-pytorch). Currently, the Linear op kernel of Weight-only quantization is implemented in the Intel-extension-for-pytorch branch: "dev/QLLM".
+Intel-extension-for-transformers implement weight-only quantization for intel GPU(PVC/ARC/MTL) with [Intel-extension-for-pytorch](https://github.com/intel/intel-extension-for-pytorch).
 
 Now 4-bit/8-bit inference with `RtnConfig`, `AwqConfig`, `GPTQConfig`, `AutoRoundConfig` are support on intel GPU device.