Manashgoswami gh pages (#8091)

* Update ort-training.md

* Update index.md

* Update index.md

* Update ort-training.md

* Update index.md

* Update install.md

* Update index.md

docs/how-to/install.md

@@ -59,12 +59,22 @@ by running `locale-gen en_US.UTF-8` and `update-locale LANG=en_US.UTF-8`
 
 
 ## Training
- 
-||Official build|Nightly build|
+
+ONNX Runtime Training packages are available for different versions of PyTorch, CUDA and ROCm versions. 
+
+The install command is:
+```cmd
+pip3 install torch-ort [-f location]
+python 3 -m torch_ort.configure
+```
+
+The _location_ needs to be specified for any specific version other than the default combination. The location for the different configurations are below:
+
+||Official build (location)|Nightly build (location)|
 |---|---|---|
 |PyTorch 1.8.1 (CUDA 10.2)|[**onnxruntime_stable_torch181.cu102**](https://onnxruntimepackages.z14.web.core.windows.net/onnxruntime_stable_torch181.cu102.html)|[onnxruntime_nightly_torch181.cu102](https://onnxruntimepackages.z14.web.core.windows.net/onnxruntime_nightly_torch181.cu102.html)|
 |PyTorch 1.8.1 (CUDA 11.1)|[**onnxruntime_stable_torch181.cu111**](https://onnxruntimepackages.z14.web.core.windows.net/onnxruntime_stable_torch181.cu111.html )|[onnxruntime_nightly_torch181.cu111](https://onnxruntimepackages.z14.web.core.windows.net/onnxruntime_nightly_torch181.cu111.html)|
-|PyTorch 1.9 (CUDA 10.2)|[**onnxruntime-training**](https://pypi.org/project/onnxruntime-training/)|[onnxruntime_nightly_torch190.cu102](https://onnxruntimepackages.z14.web.core.windows.net/onnxruntime_nightly_torch190.cu102.html)|
+|PyTorch 1.9 (CUDA 10.2) **Default**|[**onnxruntime-training**](https://pypi.org/project/onnxruntime-training/)|[onnxruntime_nightly_torch190.cu102](https://onnxruntimepackages.z14.web.core.windows.net/onnxruntime_nightly_torch190.cu102.html)|
 |PyTorch 1.9 (CUDA 11.1)|[**onnxruntime_stable_torch190.cu111**](https://onnxruntimepackages.z14.web.core.windows.net/onnxruntime_stable_torch190.cu111.html)|[onnxruntime_nightly_torch190.cu111](https://onnxruntimepackages.z14.web.core.windows.net/onnxruntime_nightly_torch190.cu111.html)|
 |[*Preview*] PyTorch 1.8.1 (ROCm 4.2)|[**onnxruntime_stable_torch181.rocm42**](https://onnxruntimepackages.z14.web.core.windows.net/onnxruntime_stable_torch181.rocm42.html)|[onnxruntime_nightly_torch181.rocm42](https://onnxruntimepackages.z14.web.core.windows.net/onnxruntime_nightly_torch181.rocm42.html)|
-|[*Preview*] PyTorch 1.9 (ROCm 4.2)|[**onnxruntime_stable_torch190.rocm42**](https://onnxruntimepackages.z14.web.core.windows.net/onnxruntime_stable_torch190.rocm42.html)|[onnxruntime_nightly_torch190.rocm42](https://onnxruntimepackages.z14.web.core.windows.net/onnxruntime_nightly_torch190.rocm42.html)|
+|[*Preview*] PyTorch 1.9 (ROCm 4.2)|[**onnxruntime_stable_torch190.rocm42**](https://onnxruntimepackages.z14.web.core.windows.net/onnxruntime_stable_torch190.rocm42.html)|[onnxruntime_nightly_torch190.rocm42](https://onnxruntimepackages.z14.web.core.windows.net/onnxruntime_nightly_torch190.rocm42.html)|

docs/index.md

@@ -55,6 +55,26 @@ Released in April 2021, ONNX Runtime Training provides a one-line addition for e
 
 Using the ORTModule class wrapper, ONNX Runtime for PyTorch runs the forward and backward passes of the training script using an optimized automatically-exported ONNX computation graph. ORT Training uses the same graph optimizations as ORT Inferencing, allowing for model training acceleration. 
 
+The ORTModule is instantiated from [`torch-ort`](https://github.com/pytorch/ort) backend in PyTorch. This new interface enables a seamless integration for ONNX Runtime training in a PyTorch training code with minimal changes to the existing code.
+
+### Install ONNX Runtime Training package
+
+`pip install torch-ort
+python -m torch_ort.configure`
+
+**Note**: This installs the default version of the `torch-ort` and `onnxruntime-training` packages that are mapped to specific versions of the CUDA libraries. Refer to the install options in [ONNXRUNTIME.ai](https://onnxruntime.ai).
+
+### Add ORTModule in the `train.py`
+
+```python
+   from torch_ort import ORTModule
+   .
+   .
+   .
+   model = ORTModule(model)
+```
+
+**Note**: the `model` where ORTModule is wrapped needs to be a derived from the `torch.nn.Module` class.
  
 
 

docs/tutorials/training/index.md

@@ -6,3 +6,4 @@ nav_order: 2
 ---
 # Tutorials: ORT Training
 
+## [Finetuning acceleration for Hugging Face Transformers with ONNX Runtime](https://github.com/microsoft/onnxruntime-training-examples/tree/master/huggingface).

docs/tutorials/training/ort-training.md

@@ -16,4 +16,5 @@ nav_order: 1
 
 * [Accelerate fine tuning of Huggingface GPT2 model](https://github.com/microsoft/onnxruntime-training-examples/tree/master/orttrainer/huggingface-gpt2)
 
+
 * *More coming soon!*