add contact group

.github/workflows/unit_test.yml

@@ -1,13 +1,23 @@
 name: Unit Tests
 
-on: 
+on:
   workflow_dispatch:
   pull_request:
+    branches:
+      - main
+    tags:
+      - r[0-9]+.[0-9]+
+    paths-ignore:
+      - 'docs/**'
+      - '**.md'
   push:
     branches:
       - main
     tags:
       - r[0-9]+.[0-9]+
+    paths-ignore:
+      - 'docs/**'
+      - '**.md'
 
 
 jobs:
@@ -26,5 +36,5 @@ jobs:
           git config --global --add safe.directory $PWD && \
           pip install -e . && \
           bash tests/run_ut.sh'
-      env: 
+      env:
         UT_IMAGE: ${{ secrets.UT_IMAGE }}

README.md

@@ -3,15 +3,15 @@
 [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://github.com/alibabapai/torchacc/blob/main/LICENSE)
 
 # TorchAcc
-
-**TorchAcc** is an AI training acceleration framework developed by Alibaba Cloud’s PAI.
+**TorchAcc** is an AI training acceleration framework developed by Alibaba Cloud’s PAI team.
 
 TorchAcc is built on [PyTorch/XLA](https://github.com/pytorch/xla) and provides an easy-to-use interface to accelerate the training of PyTorch models. At the same time, TorchAcc has implemented extensive optimizations for distributed training, memory management, and computation specifically for GPUs, ultimately achieving improved ease of use, better GPU training performance, and enhanced scalability for distributed training.
 
+[**Documentation**](https://torchacc.readthedocs.io/en/latest/)
 
 ## Highlighted Features
 
-* Rich distributed Parallelism
+* Rich distributed parallelism strategies
     * Data Parallelism
     * Fully Sharded Data Parallelism
     * Tensor Parallelism
@@ -20,7 +20,7 @@ TorchAcc is built on [PyTorch/XLA](https://github.com/pytorch/xla) and provides
       * [Ulysess](https://arxiv.org/abs/2309.14509)
       * [Ring Attention](https://arxiv.org/abs/2310.01889)
       * FlashSequence (2D Sequence Parallelism)
-* Low Memory Cost
+* Memory efficient
 * High Performance
 * Easy-to-use API
 
@@ -53,32 +53,41 @@ sudo docker run  --gpus all --net host --ipc host --shm-size 10G -it --rm --cap-
 see the [contribution guide](docs/source/contributing.md).
 
 
-## LLMs training examples
-
-### Getting Started
+## Getting Started
 
 We present a straightforward example for training a Transformer model using TorchAcc, illustrating the usage of the TorchAcc API.
 You can quickly initiate training a Transformer model with TorchAcc by executing the following command:
 ``` shell
 torchrun --nproc_per_node=4 benchmarks/transformer.py --bf16 --acc --disable_loss_print --fsdp_size=4 --gc
 ```
 
+## LLMs training examples
+
 ### Utilizing HuggingFace Transformers
 
 If you are familiar with HuggingFace Transformers's Trainer, you can easily accelerate a Transformer model using TorchAcc, see the [huggingface transformers](docs/source/tutorials/hf_transformers.md)
 
 ### LLMs training acceleration with FlashModels
 
-If you want to try the latest features of Torchacc or want to use the TorchAcc interface more flexibly for model acceleration, you can use our LLM acceleration library, FlashModels. It integrates various distributed implementations of commonly used open-source LLM models and provides a wealth of examples.
+If you want to try the latest features of Torchacc or want to use the TorchAcc interface more flexibly for model acceleration, you can use our LLM acceleration library, FlashModels. FlashModels integrates various distributed implementations of commonly used open-source LLMs and provides a wealth of examples and benchmarks.
 
 https://github.com/AlibabaPAI/FlashModels
 
 ### SFT using modelscope/swift
 coming soon..
 
+
 ## Contributing
 see the [contribution guide](docs/source/contributing.md).
 
 
+## Contact Us
+
+You can contact us by adding our DingTalk group:
+
+<p align="center">
+  <img width="30%" src=docs/figures/group.png />
+</p>
+
 ## License
 [Apache License 2.0](LICENSE)

docs/source/conf.py

@@ -9,7 +9,7 @@
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information
 import datetime
 
-project = 'PAI-TorchAcc'
+project = 'TorchAcc'
 copyright = '2024, alibaba-cloud'
 author = 'Alibaba Cloud'
 release = '2.3.0'

docs/source/index.rst

@@ -1,9 +1,9 @@
-.. PAI-TorchAcc documentation master file, created by
+.. TorchAcc documentation master file, created by
    sphinx-quickstart on Fri Nov  3 16:11:35 2023.
    You can adapt this file completely to your liking, but it should at least
    contain the root `toctree` directive.
 
-Welcome to PAI-TorchAcc's documentation!
+Welcome to TorchAcc's documentation!
 ========================================
 
 .. toctree::