LLM: refactor gpu examples (#8963)

* restructure

* change to hf-transformers-models/

python/llm/example/gpu/README.md

@@ -1,5 +1,20 @@
-# BigDL-LLM Transformers INT4 Optimization for Large Language Model on Intel GPUs
-You can use BigDL-LLM to run almost every Huggingface Transformer models with INT4 optimizations on your laptops with Intel GPUs. This directory contains example scripts to help you quickly get started using BigDL-LLM to run some popular open-source models in the community. Each model has its own dedicated folder, where you can find detailed instructions on how to install and run it.
+# BigDL-LLM INT4 Optimization for Large Language Model on Intel GPUs
+You can use BigDL-LLM to run almost every Huggingface Transformer models with INT4 optimizations on your laptops with Intel GPUs. Moreover, you can also use `optimize_model` API to accelerate general PyTorch models on Intel GPUs.
+
+## Verified models
+| Model      | Example                                                  |
+|------------|----------------------------------------------------------|
+| Baichuan   | [link](hf-transformers-models/baichuan)          | 
+| ChatGLM2   | [link](hf-transformers-models/chatglm2)          |
+| Chinese Llama2 | [link](hf-transformers-models/chinese-llama2)|
+| Falcon     | [link](hf-transformers-models/falcon)            |
+| GPT-J      | [link](hf-transformers-models/gpt-j)             |
+| InternLM   | [link](hf-transformers-models/internlm)          |
+| LLaMA 2    | [link](hf-transformers-models/llama2)            |
+| MPT        | [link](hf-transformers-models/mpt)               |
+| Qwen       | [link](hf-transformers-models/qwen)              |
+| StarCoder  | [link](hf-transformers-models/starcoder)         |
+| Whisper    | [link](hf-transformers-models/whisper)           |
 
 ## Verified Hardware Platforms
 

python/llm/example/gpu/hf-transformers-models/README.md

@@ -0,0 +1,40 @@
+# BigDL-LLM Transformers INT4 Optimization for Large Language Model on Intel GPUs
+You can use BigDL-LLM to run almost every Huggingface Transformer models with INT4 optimizations on your laptops with Intel GPUs. This directory contains example scripts to help you quickly get started using BigDL-LLM to run some popular open-source models in the community. Each model has its own dedicated folder, where you can find detailed instructions on how to install and run it.
+
+## Verified models
+| Model      | Example                                                  |
+|------------|----------------------------------------------------------|
+| Baichuan   | [link](baichuan)          | 
+| ChatGLM2   | [link](chatglm2)          |
+| Chinese Llama2 | [link](chinese-llama2)|
+| Falcon     | [link](falcon)            |
+| GPT-J      | [link](gpt-j)             |
+| InternLM   | [link](internlm)          |
+| LLaMA 2    | [link](llama2)            |
+| MPT        | [link](mpt)               |
+| Qwen       | [link](qwen)              |
+| StarCoder  | [link](starcoder)         |
+| Whisper    | [link](whisper)           |
+
+## Verified Hardware Platforms
+
+- Intel Arc™ A-Series Graphics
+- Intel Data Center GPU Flex Series
+
+## Recommended Requirements
+To apply Intel GPU acceleration, there’re several steps for tools installation and environment preparation.
+
+Step 1, only Linux system is supported now, Ubuntu 22.04 is prefered.
+
+Step 2, please refer to our [driver installation](https://dgpu-docs.intel.com/driver/installation.html) for general purpose GPU capabilities.
+> **Note**: IPEX 2.0.110+xpu requires Intel GPU Driver version is [Stable 647.21](https://dgpu-docs.intel.com/releases/stable_647_21_20230714.html).
+
+Step 3, you also need to download and install [Intel® oneAPI Base Toolkit](https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit-download.html). OneMKL and DPC++ compiler are needed, others are optional.
+> **Note**: IPEX 2.0.110+xpu requires Intel® oneAPI Base Toolkit's version >= 2023.2.0.
+
+## Best Known Configuration on Linux
+For better performance, it is recommended to set environment variables on Linux:
+```bash
+export USE_XETLA=OFF
+export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1
+```

python/llm/example/gpu/pytorch-models/README.md

@@ -0,0 +1,25 @@
+# BigDL-LLM INT4 Optimization for Large Language Model on Intel GPUs
+You can use `optimize_model` API to accelerate general PyTorch models on Intel servers and PCs. This directory contains example scripts to help you quickly get started using BigDL-LLM to run some popular open-source models in the community. Each model has its own dedicated folder, where you can find detailed instructions on how to install and run it.
+
+## Verified Hardware Platforms
+
+- Intel Arc™ A-Series Graphics
+- Intel Data Center GPU Flex Series
+
+## Recommended Requirements
+To apply Intel GPU acceleration, there’re several steps for tools installation and environment preparation.
+
+Step 1, only Linux system is supported now, Ubuntu 22.04 is prefered.
+
+Step 2, please refer to our [driver installation](https://dgpu-docs.intel.com/driver/installation.html) for general purpose GPU capabilities.
+> **Note**: IPEX 2.0.110+xpu requires Intel GPU Driver version is [Stable 647.21](https://dgpu-docs.intel.com/releases/stable_647_21_20230714.html).
+
+Step 3, you also need to download and install [Intel® oneAPI Base Toolkit](https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit-download.html). OneMKL and DPC++ compiler are needed, others are optional.
+> **Note**: IPEX 2.0.110+xpu requires Intel® oneAPI Base Toolkit's version >= 2023.2.0.
+
+## Best Known Configuration on Linux
+For better performance, it is recommended to set environment variables on Linux:
+```bash
+export USE_XETLA=OFF
+export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1
+```