Update docs and README

README.md

@@ -27,7 +27,8 @@ For more details, please refer to our paper ["Qlib: An AI-oriented Quantitative
   - [Data Preparation](#data-preparation)
   - [Auto Quant Research Workflow](#auto-quant-research-workflow)
   - [Building Customized Quant Research Workflow by Code](#building-customized-quant-research-workflow-by-code)
-- [Quant Model Zoo](#quant-model-zoo)
+  - [Run a single model](#run-a-single-model)
+  - [Run multiple models](#run-multiple-models)
 - [Quant Dataset Zoo](#quant-dataset-zoo)
 - [More About Qlib](#more-about-qlib)
 - [Offline Mode and Online Mode](#offline-mode-and-online-mode)
@@ -188,7 +189,25 @@ Qlib provides a tool named `qrun` to run the whole workflow automatically (inclu
 The automatic workflow may not suite the research workflow of all Quant researchers. To support a flexible Quant research workflow, Qlib also provides a modularized interface to allow researchers to build their own workflow by code. [Here](examples/workflow_by_code.ipynb) is a demo for customized Quant research workflow by code.
 
 
-# Quant Model Zoo
+[# Quant Model Zoo](examples/benchmarks)
+
+## Run a single model
+`Qlib` provides three different ways to run a single model, users can pick the one that fits their cases best:
+- User can use the tool `qrun` mentioned above to run a model's workflow based from a config file.
+- User can create a `workflow_by_code` python script based on the [one](examples/workflow_by_code.py) listed in the `examples` folder.
+- User can use the script [`run_all_model.py`](examples/run_all_model.py) listed in the `examples` folder to run a model. Here is an example of the specific shell command to be used: `python run_all_model.py --models=lightgbm`. For more use cases, please refer to the file's [docstrings](examples/run_all_model.py).
+
+## Run multiple models
+`Qlib` also provides a script [`run_all_model.py`](examples/run_all_model.py) which can run multiple models for several iterations. (**Note**: the script only supprots *Linux* now. Other OS will be supported in the future.)
+
+The script will create a unique virtual environment for each model, and delete the environments after training. Thus, only experiment results such as `IC` and `backtest` results will be generated and stored. 
+
+Here is an example of running all the models for 10 iterations:
+```python
+python run_all_model.py 10
+```
+
+It also provides the API to run specific models at once. For more use cases, please refer to the file's [docstrings](examples/run_all_model.py). 
 
 Here is a list of models built on `Qlib`.
 - [GBDT based on LightGBM](qlib/contrib/model/gbdt.py)