update IPEX version in doc for 2.8 release (#5730)

Signed-off-by: Neo Zhang Jianyu <[email protected]>

Author: NeoZhangJianyu

docs/tutorials/llm.rst

@@ -136,7 +136,7 @@ LLM fine-tuning on Intel® Data Center Max 1550 GPU
      - ✅
 
 
-Check `LLM best known practice <https://github.com/intel/intel-extension-for-pytorch/tree/release/xpu/2.7.10/examples/gpu/llm>`_ for instructions to install/setup environment and example scripts..
+Check `LLM best known practice <https://github.com/intel/intel-extension-for-pytorch/tree/release/xpu/2.8.10/examples/gpu/llm>`_ for instructions to install/setup environment and example scripts..
 
 Optimization Methodologies
 --------------------------

docs/tutorials/llm/int4_weight_only_quantization.md

@@ -129,9 +129,9 @@ Intel® Extension for PyTorch\* implements Weight-Only Quantization for Intel®
 
 ### Environment Setup
 
-Please refer to the [env setup](https://github.com/intel/intel-extension-for-pytorch/blob/v2.7.10%2Bxpu/examples/gpu/llm/inference/README.md).
+Please refer to the [env setup](https://github.com/intel/intel-extension-for-pytorch/blob/v2.8.10%2Bxpu/examples/gpu/llm/inference/README.md).
 
-Example can be found at [Learn WOQ](https://github.com/intel/intel-extension-for-pytorch/tree/v2.7.10%2Bxpu/examples/gpu/llm/inference#learn-to-quantize-llm-and-run-inference).
+Example can be found at [Learn WOQ](https://github.com/intel/intel-extension-for-pytorch/tree/v2.8.10%2Bxpu/examples/gpu/llm/inference#learn-to-quantize-llm-and-run-inference).
 
 ### Run Weight-Only Quantization LLM on Intel® GPU
 
@@ -182,7 +182,7 @@ output = loaded_model.generate(inputs)
 ```
 
 
-#### Execute [WOQ benchmark script](https://github.com/intel/intel-extension-for-pytorch/blob/v2.7.10%2Bxpu/examples/gpu/llm/inference/run_benchmark_woq.sh)
+#### Execute [WOQ benchmark script](https://github.com/intel/intel-extension-for-pytorch/blob/v2.8.10%2Bxpu/examples/gpu/llm/inference/run_benchmark_woq.sh)
 
 ```python
 bash run_benchmark_woq.sh

docs/tutorials/llm/llm_optimize_transformers.md

@@ -9,7 +9,7 @@ API documentation is available at [API Docs page](../api_doc.html#ipex.llm.optim
 
 ## Pseudocode of Common Usage Scenarios
 
-The following sections show pseudocode snippets to invoke Intel® Extension for PyTorch\* APIs to work with LLMs. Complete examples can be found at [the Example directory](https://github.com/intel/intel-extension-for-pytorch/tree/v2.7.10%2Bxpu/examples/gpu/llm/inference).
+The following sections show pseudocode snippets to invoke Intel® Extension for PyTorch\* APIs to work with LLMs. Complete examples can be found at [the Example directory](https://github.com/intel/intel-extension-for-pytorch/tree/v2.8.10%2Bxpu/examples/gpu/llm/inference).
 
 ### FP16
 

examples/gpu/llm/README.md

@@ -3,7 +3,7 @@
 Here you can find examples for large language models (LLM) text generation. These scripts:
 
 > [!NOTE]  
-> New Llama models like Llama3.2-1B, Llama3.2-3B and Llama3.3-7B are also supported from release v2.7.10+xpu.
+> New Llama models like Llama3.2-1B, Llama3.2-3B and Llama3.3-7B are also supported from release v2.8.10+xpu.
 
 - Include both inference/finetuning(lora)/bitsandbytes(qlora-finetuning).
 - Include both single instance and distributed (DeepSpeed) use cases for FP16 optimization.
@@ -18,7 +18,7 @@ Here you can find examples for large language models (LLM) text generation. Thes
 # Get the Intel® Extension for PyTorch* source code
 git clone https://github.com/intel/intel-extension-for-pytorch.git
 cd intel-extension-for-pytorch
-git checkout release/xpu/2.7.10
+git checkout release/xpu/2.8.10
 git submodule sync
 git submodule update --init --recursive
 
@@ -38,14 +38,14 @@ call .\tools\env_activate.bat [inference|fine-tuning|bitsandbytes]
 ```
 ### Conda-based environment setup with prebuilt release wheel files
 
-Make sure the driver packages are installed. Refer to [Installation Guide](https://intel.github.io/intel-extension-for-pytorch/#installation?platform=gpu&version=v2.7.10%2Bxpu&os=linux%2Fwsl2&package=pip).
+Make sure the driver packages are installed. Refer to [Installation Guide](https://intel.github.io/intel-extension-for-pytorch/#installation?platform=gpu&version=v2.8.10%2Bxpu&os=linux%2Fwsl2&package=pip).
 
 ```bash
 
 # Get the Intel® Extension for PyTorch* source code
 git clone https://github.com/intel/intel-extension-for-pytorch.git
 cd intel-extension-for-pytorch
-git checkout release/xpu/2.7.10
+git checkout release/xpu/2.8.10
 git submodule sync
 git submodule update --init --recursive