Minor doc fixes (#417)

* Update installation instructions

* Format fix

* ZeRO tutorial

* Format fixes

* ZeRO-Offload

* ZeRO and ZeRO-Offload tutorials

* Update navigation page

* Format fixes

* Add yuxhe feedback

* Fix blog post link

* Fix OneBit-Adam link
Tweak scheduler example

* Fix date link
Co-authored-by: Shaden Smith <Shaden.Smith@microsoft.com>
Co-authored-by: Jeff Rasley <jerasley@microsoft.com>

docs/_pages/config-json.md

@@ -78,8 +78,8 @@ title: "DeepSpeed Configuration JSON"
 
 | Fields | Value                                                        | Example                        |
 | ------ | ------------------------------------------------------------ | ------------------------------ |
-| type   | The scheduler name. See [here](https://deepspeed.readthedocs.io/en/latest/deepspeed.pt.html) for list of support schedulers. | `"1Cycle"`                      |
-| params | Dictionary of parameters to instantiate scheduler. The parameter names should match scheduler constructor signature. | `{"lr": 0.001, "eps": 1e-8}` |
+| type   | The scheduler name. See [here](https://deepspeed.readthedocs.io/en/latest/deepspeed.pt.html) for list of support schedulers. | `"WarmupLR"`                      |
+| params | Dictionary of parameters to instantiate scheduler. The parameter names should match scheduler constructor signature. | `{"warmup_min_lr": 0, "warmup_max_lr": 0.001}` |
 
 Example of ***scheduler***
 

docs/_posts/2020-09-09-onebit-adam-news.md

@@ -16,6 +16,6 @@ across distributed devices. We introduce a new algorithm - 1-bit Adam - and
 its efficient implementation in DeepSpeed. 1-bit Adam offers the ***same convergence*** as Adam, incurs up to ***5x less communication*** that enables up to ***3.5x higher throughput for BERT-Large pretraining*** and up to ***2.7x higher throughput for SQuAD fine-tuning*** on bandwidth-limited clusters.
 
 * Brief overview, see our [press release]({{ site.press_release_v3 }}).
-* Detailed technology deep dive, see our [blog post](https://www.deepspeed.ai/news/2020/09/09/onebit-adam-blog-post.html).
+* Detailed technology deep dive, see our [blog post](https://www.deepspeed.ai/news/2020/09/08/onebit-adam-blog-post.html).
 * Tutorial on how to reproduce our results, see our [1-bit Adam tutorial](/tutorials/onebit-adam/).
 * The source code for 1-bit Adam can be found in the [DeepSpeed repo](https://github.com/microsoft/deepspeed). The implementation of 1-bit Adam is in [onebit_adam.py](https://github.com/microsoft/DeepSpeed/blob/master/deepspeed/runtime/fp16/onebit_adam.py) and CUDA-Aware communication for 1-bit Adam is in [custom_collectives.py](https://github.com/microsoft/DeepSpeed/blob/master/deepspeed/runtime/custom_collectives.py). Example codes to try this feature can be found in the [DeepSpeedExamples repo](https://github.com/microsoft/deepspeedexamples) as shown in the [tutorial](/tutorials/onebit-adam/).

docs/_tutorials/onebit-adam.md

@@ -2,7 +2,7 @@
 title: "1-bit Adam: Up to 5x less communication volume and up to 2x faster training"
 ---
 
-In this tutorial, we are going to introduce the 1-bit Adam optimizer in DeepSpeed. 1-bit Adam can improve model training speed on communication-constrained clusters, especially for communication-intensive large models by reducing the overall communication volume by up to 5x. Detailed description of the 1-bit Adam algorithm, its implementation in DeepSpeed, and performance evaluation is available from our [blog post](https://www.deepspeed.ai/news/2020/09/09/onebit-adam-blog-post.html).
+In this tutorial, we are going to introduce the 1-bit Adam optimizer in DeepSpeed. 1-bit Adam can improve model training speed on communication-constrained clusters, especially for communication-intensive large models by reducing the overall communication volume by up to 5x. Detailed description of the 1-bit Adam algorithm, its implementation in DeepSpeed, and performance evaluation is available from our [blog post](https://www.deepspeed.ai/news/2020/09/08/onebit-adam-blog-post.html).
 
 To illustrate the benefits and usage of 1-bit Adam optimizer in DeepSpeed, we use the following two training tasks as examples: