LLM: update key feature and installation page of document (#9068)

docs/readthedocs/source/_toc.yml

@@ -38,12 +38,12 @@ subtrees:
             title: "Key Features"
             subtrees:
               - entries:
+                - file: doc/LLM/Overview/KeyFeatures/optimize_model
                 - file: doc/LLM/Overview/KeyFeatures/transformers_style_api
                   subtrees:
                     - entries:
                       - file: doc/LLM/Overview/KeyFeatures/hugging_face_format
                       - file: doc/LLM/Overview/KeyFeatures/native_format
-                - file: doc/LLM/Overview/KeyFeatures/optimize_model
                 - file: doc/LLM/Overview/KeyFeatures/langchain_api
                 # - file: doc/LLM/Overview/KeyFeatures/cli
                 - file: doc/LLM/Overview/KeyFeatures/gpu_supports

docs/readthedocs/source/doc/LLM/Overview/KeyFeatures/index.rst

@@ -3,12 +3,12 @@ BigDL-LLM Key Features
 
 You may run the LLMs using ``bigdl-llm`` through one of the following APIs:
 
+* `PyTorch API <./optimize_model.html>`_
 * |transformers_style_api|_
 
   * |hugging_face_transformers_format|_
   * `Native Format <./native_format.html>`_
 
-* `General PyTorch Model Supports <./langchain_api.html>`_
 * `LangChain API <./langchain_api.html>`_
 * `GPU Supports <./gpu_supports.html>`_
 

docs/readthedocs/source/doc/LLM/Overview/KeyFeatures/optimize_model.md

@@ -1,22 +1,27 @@
-## General PyTorch Model Supports
+## PyTorch API
 
-You may apply BigDL-LLM optimizations on any Pytorch models, not only Hugging Face *Transformers* models for acceleration. With BigDL-LLM, PyTorch models (in FP16/BF16/FP32) can be optimized with low-bit quantizations (supported precisions include INT4/INT5/INT8).
+In general, you just need one-line `optimize_model` to easily optimize any loaded PyTorch model, regardless of the library or API you are using. With BigDL-LLM, PyTorch models (in FP16/BF16/FP32) can be optimized with low-bit quantizations (supported precisions include INT4, INT5, INT8, etc).
 
-You can easily enable BigDL-LLM INT4 optimizations on any Pytorch models just as follows:
+First, use any PyTorch APIs you like to load your model. To help you better understand the process, here we use [Hugging Face Transformers](https://huggingface.co/docs/transformers/index) library `LlamaForCausalLM` to load a popular model [Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf) as an example:
 
 ```python
-# Create or load any Pytorch model
-model = ...
+# Create or load any Pytorch model, take Llama-2-7b-chat-hf as an example
+from transformers import LlamaForCausalLM
+model = LlamaForCausalLM.from_pretrained('meta-llama/Llama-2-7b-chat-hf', torch_dtype='auto', low_cpu_mem_usage=True)
+```
 
-# Add only two lines to enable BigDL-LLM INT4 optimizations on model
+Then, just need to call `optimize_model` to optimize the loaded model and INT4 optimization is applied on model by default: 
+```python
 from bigdl.llm import optimize_model
+
+# With only one line to enable BigDL-LLM INT4 optimization
 model = optimize_model(model)
 ```
 
-After optimizing the model, you may straightly run the optimized model with no API changed and less inference latency.
+After optimizing the model, BigDL-LLM does not require any change in the inference code. You can use any libraries to run the optimized model with very low latency.
 
 ```eval_rst
 .. seealso::
 
-   See the examples for Hugging Face *Transformers* models `here <https://github.com/intel-analytics/BigDL/blob/main/python/llm/example/transformers/general_int4>`_. And examples for other general Pytorch models can be found `here <https://github.com/intel-analytics/BigDL/blob/main/python/llm/example/pytorch-model>`_.
+   * For more detailed usage of ``optimize_model``, please refer to the `API documentation <https://bigdl.readthedocs.io/en/latest/doc/PythonAPI/LLM/optimize.html>`_.
 ```

docs/readthedocs/source/doc/LLM/Overview/install_cpu.md

@@ -5,9 +5,11 @@
 Install BigDL-LLM for CPU supports using pip through:
 
 ```bash
-pip install bigdl-llm[all]
+pip install --pre --upgrade bigdl-llm[all] # install the latest bigdl-llm nightly build with 'all' option
 ```
 
+Please refer to [Environment Setup](#environment-setup) for more information.
+
 ```eval_rst
 .. note::
 
@@ -43,7 +45,7 @@ First we recommend using [Conda](https://docs.conda.io/en/latest/miniconda.html)
 conda create -n llm python=3.9
 conda activate llm
 
-pip install bigdl-llm[all] # install bigdl-llm for CPU with 'all' option
+pip install --pre --upgrade bigdl-llm[all] # install the latest bigdl-llm nightly build with 'all' option
 ```
 
 Then for running a LLM model with BigDL-LLM optimizations (taking an `example.py` an example):

docs/readthedocs/source/doc/LLM/Overview/install_gpu.md

@@ -5,9 +5,11 @@
 Install BigDL-LLM for GPU supports using pip through:
 
 ```bash
-pip install --pre --upgrade bigdl-llm[xpu] -f https://developer.intel.com/ipex-whl-stable-xpu
+pip install --pre --upgrade bigdl-llm[xpu] -f https://developer.intel.com/ipex-whl-stable-xpu # install bigdl-llm for GPU
 ```
 
+Please refer to [Environment Setup](#environment-setup) for more information.
+
 ```eval_rst
 .. note::
 
@@ -25,6 +27,12 @@ BigDL-LLM for GPU supports has been verified on:
 * Intel Arc™ A-Series Graphics
 * Intel Data Center GPU Flex Series
 
+```eval_rst
+.. note::
+
+   We currently supoort the Ubuntu 20.04 operating system or later. Windows supoort is in progress.
+```
+
 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.

docs/readthedocs/source/doc/LLM/index.rst

@@ -32,8 +32,8 @@ BigDL-LLM
 
         +++
 
+        :bdg-link:`PyTorch <./Overview/KeyFeatures/optimize_model.html>` |
         :bdg-link:`transformers-style <./Overview/KeyFeatures/transformers_style_api.html>` |
-        :bdg-link:`Optimize Model <./Overview/KeyFeatures/optimize_model.html>` |
         :bdg-link:`LangChain <./Overview/KeyFeatures/langchain_api.html>` |
         :bdg-link:`GPU <./Overview/KeyFeatures/gpu_supports.html>`
 

docs/readthedocs/source/doc/PythonAPI/LLM/index.rst

@@ -4,6 +4,6 @@ BigDL-LLM API
 .. toctree::
     :maxdepth: 3
 
+    optimize.rst
     transformers.rst
     langchain.rst
-    optimize.rst

docs/readthedocs/source/doc/PythonAPI/LLM/optimize.rst

@@ -1,4 +1,4 @@
-BigDL-LLM Optimize API
+BigDL-LLM PyTorch API
 =====================
 
 llm.optimize