From b0ce5a10326912961f0bc07cbbd250bab7b9c399 Mon Sep 17 00:00:00 2001
From: Fazzie-Maqianli <55798671+Fazziekey@users.noreply.github.com>
Date: Tue, 28 Mar 2023 20:25:36 +0800
Subject: [PATCH] [Coati] first commit (#3283)
---
applications/Chat/.gitignore | 146 +++++++++
applications/Chat/LICENSE | 202 +++++++++++++
applications/Chat/README.md | 269 +++++++++++++++++
applications/Chat/assets/data-collect.png | Bin 0 -> 410749 bytes
applications/Chat/assets/logo_coati.png | Bin 0 -> 655366 bytes
applications/Chat/assets/stage-3.jpeg | Bin 0 -> 378888 bytes
applications/Chat/benchmarks/README.md | 94 ++++++
.../Chat/benchmarks/benchmark_gpt_dummy.py | 184 ++++++++++++
.../Chat/benchmarks/benchmark_gpt_dummy.sh | 45 +++
.../benchmarks/benchmark_opt_lora_dummy.py | 179 +++++++++++
applications/Chat/coati/__init__.py | 0
applications/Chat/coati/dataset/__init__.py | 9 +
.../Chat/coati/dataset/prompt_dataset.py | 46 +++
.../Chat/coati/dataset/reward_dataset.py | 112 +++++++
.../Chat/coati/dataset/sft_dataset.py | 169 +++++++++++
applications/Chat/coati/dataset/utils.py | 22 ++
.../Chat/coati/experience_maker/__init__.py | 4 +
.../Chat/coati/experience_maker/base.py | 77 +++++
.../Chat/coati/experience_maker/naive.py | 35 +++
applications/Chat/coati/models/__init__.py | 4 +
.../Chat/coati/models/base/__init__.py | 6 +
applications/Chat/coati/models/base/actor.py | 65 ++++
applications/Chat/coati/models/base/critic.py | 54 ++++
applications/Chat/coati/models/base/lm.py | 30 ++
.../Chat/coati/models/base/reward_model.py | 41 +++
.../Chat/coati/models/bloom/__init__.py | 6 +
.../Chat/coati/models/bloom/bloom_actor.py | 35 +++
.../Chat/coati/models/bloom/bloom_critic.py | 38 +++
.../Chat/coati/models/bloom/bloom_lm.py | 35 +++
.../Chat/coati/models/bloom/bloom_rm.py | 37 +++
.../Chat/coati/models/deberta/__init__.py | 4 +
.../coati/models/deberta/deberta_critic.py | 36 +++
.../Chat/coati/models/deberta/deberta_rm.py | 37 +++
applications/Chat/coati/models/generation.py | 146 +++++++++
.../Chat/coati/models/generation_utils.py | 92 ++++++
.../Chat/coati/models/gpt/__init__.py | 6 +
.../Chat/coati/models/gpt/gpt_actor.py | 35 +++
.../Chat/coati/models/gpt/gpt_critic.py | 37 +++
applications/Chat/coati/models/gpt/gpt_lm.py | 35 +++
applications/Chat/coati/models/gpt/gpt_rm.py | 39 +++
.../Chat/coati/models/llama/__init__.py | 6 +
.../Chat/coati/models/llama/llama_actor.py | 38 +++
.../Chat/coati/models/llama/llama_critic.py | 42 +++
.../Chat/coati/models/llama/llama_lm.py | 40 +++
.../Chat/coati/models/llama/llama_rm.py | 40 +++
applications/Chat/coati/models/lora.py | 129 ++++++++
applications/Chat/coati/models/loss.py | 117 ++++++++
.../Chat/coati/models/opt/__init__.py | 6 +
.../Chat/coati/models/opt/opt_actor.py | 35 +++
.../Chat/coati/models/opt/opt_critic.py | 38 +++
applications/Chat/coati/models/opt/opt_lm.py | 35 +++
applications/Chat/coati/models/opt/opt_rm.py | 38 +++
applications/Chat/coati/models/utils.py | 92 ++++++
.../Chat/coati/replay_buffer/__init__.py | 4 +
applications/Chat/coati/replay_buffer/base.py | 43 +++
.../Chat/coati/replay_buffer/naive.py | 57 ++++
.../Chat/coati/replay_buffer/utils.py | 73 +++++
applications/Chat/coati/trainer/__init__.py | 6 +
applications/Chat/coati/trainer/base.py | 168 +++++++++++
.../Chat/coati/trainer/callbacks/__init__.py | 5 +
.../Chat/coati/trainer/callbacks/base.py | 39 +++
.../callbacks/performance_evaluator.py | 133 ++++++++
.../trainer/callbacks/save_checkpoint.py | 75 +++++
applications/Chat/coati/trainer/ppo.py | 135 +++++++++
applications/Chat/coati/trainer/rm.py | 135 +++++++++
applications/Chat/coati/trainer/sft.py | 158 ++++++++++
.../Chat/coati/trainer/strategies/__init__.py | 6 +
.../Chat/coati/trainer/strategies/base.py | 136 +++++++++
.../coati/trainer/strategies/colossalai.py | 213 +++++++++++++
.../Chat/coati/trainer/strategies/ddp.py | 93 ++++++
.../Chat/coati/trainer/strategies/naive.py | 55 ++++
.../Chat/coati/trainer/strategies/sampler.py | 32 ++
applications/Chat/coati/trainer/utils.py | 5 +
applications/Chat/coati/utils/__init__.py | 3 +
.../Chat/coati/utils/tokenizer_utils.py | 78 +++++
applications/Chat/examples/README.md | 141 +++++++++
applications/Chat/examples/inference.py | 59 ++++
applications/Chat/examples/requirements.txt | 2 +
applications/Chat/examples/test_ci.sh | 97 ++++++
applications/Chat/examples/train_dummy.py | 148 +++++++++
applications/Chat/examples/train_dummy.sh | 18 ++
applications/Chat/examples/train_prompts.py | 199 ++++++++++++
applications/Chat/examples/train_prompts.sh | 18 ++
.../Chat/examples/train_reward_model.py | 160 ++++++++++
applications/Chat/examples/train_rm.sh | 8 +
applications/Chat/examples/train_sft.py | 184 ++++++++++++
applications/Chat/examples/train_sft.sh | 12 +
applications/Chat/inference/README.md | 111 +++++++
applications/Chat/inference/benchmark.py | 132 ++++++++
.../Chat/inference/llama_gptq/__init__.py | 5 +
.../Chat/inference/llama_gptq/loader.py | 41 +++
.../Chat/inference/llama_gptq/model_utils.py | 13 +
.../Chat/inference/llama_gptq/quant.py | 283 ++++++++++++++++++
applications/Chat/inference/locustfile.py | 27 ++
applications/Chat/inference/requirements.txt | 10 +
applications/Chat/inference/server.py | 165 ++++++++++
.../Chat/inference/tests/test_chat_prompt.py | 56 ++++
applications/Chat/inference/utils.py | 179 +++++++++++
applications/Chat/pytest.ini | 6 +
applications/Chat/requirements-test.txt | 1 +
applications/Chat/requirements.txt | 13 +
applications/Chat/setup.py | 41 +++
applications/Chat/tests/__init__.py | 0
applications/Chat/tests/test_checkpoint.py | 98 ++++++
applications/Chat/tests/test_data.py | 122 ++++++++
applications/Chat/version.txt | 1 +
106 files changed, 7069 insertions(+)
create mode 100644 applications/Chat/.gitignore
create mode 100644 applications/Chat/LICENSE
create mode 100644 applications/Chat/README.md
create mode 100644 applications/Chat/assets/data-collect.png
create mode 100644 applications/Chat/assets/logo_coati.png
create mode 100644 applications/Chat/assets/stage-3.jpeg
create mode 100644 applications/Chat/benchmarks/README.md
create mode 100644 applications/Chat/benchmarks/benchmark_gpt_dummy.py
create mode 100755 applications/Chat/benchmarks/benchmark_gpt_dummy.sh
create mode 100644 applications/Chat/benchmarks/benchmark_opt_lora_dummy.py
create mode 100644 applications/Chat/coati/__init__.py
create mode 100644 applications/Chat/coati/dataset/__init__.py
create mode 100644 applications/Chat/coati/dataset/prompt_dataset.py
create mode 100644 applications/Chat/coati/dataset/reward_dataset.py
create mode 100644 applications/Chat/coati/dataset/sft_dataset.py
create mode 100644 applications/Chat/coati/dataset/utils.py
create mode 100644 applications/Chat/coati/experience_maker/__init__.py
create mode 100644 applications/Chat/coati/experience_maker/base.py
create mode 100644 applications/Chat/coati/experience_maker/naive.py
create mode 100644 applications/Chat/coati/models/__init__.py
create mode 100644 applications/Chat/coati/models/base/__init__.py
create mode 100644 applications/Chat/coati/models/base/actor.py
create mode 100644 applications/Chat/coati/models/base/critic.py
create mode 100644 applications/Chat/coati/models/base/lm.py
create mode 100644 applications/Chat/coati/models/base/reward_model.py
create mode 100644 applications/Chat/coati/models/bloom/__init__.py
create mode 100644 applications/Chat/coati/models/bloom/bloom_actor.py
create mode 100644 applications/Chat/coati/models/bloom/bloom_critic.py
create mode 100644 applications/Chat/coati/models/bloom/bloom_lm.py
create mode 100644 applications/Chat/coati/models/bloom/bloom_rm.py
create mode 100644 applications/Chat/coati/models/deberta/__init__.py
create mode 100644 applications/Chat/coati/models/deberta/deberta_critic.py
create mode 100644 applications/Chat/coati/models/deberta/deberta_rm.py
create mode 100644 applications/Chat/coati/models/generation.py
create mode 100644 applications/Chat/coati/models/generation_utils.py
create mode 100644 applications/Chat/coati/models/gpt/__init__.py
create mode 100644 applications/Chat/coati/models/gpt/gpt_actor.py
create mode 100644 applications/Chat/coati/models/gpt/gpt_critic.py
create mode 100644 applications/Chat/coati/models/gpt/gpt_lm.py
create mode 100644 applications/Chat/coati/models/gpt/gpt_rm.py
create mode 100644 applications/Chat/coati/models/llama/__init__.py
create mode 100644 applications/Chat/coati/models/llama/llama_actor.py
create mode 100644 applications/Chat/coati/models/llama/llama_critic.py
create mode 100644 applications/Chat/coati/models/llama/llama_lm.py
create mode 100644 applications/Chat/coati/models/llama/llama_rm.py
create mode 100644 applications/Chat/coati/models/lora.py
create mode 100644 applications/Chat/coati/models/loss.py
create mode 100644 applications/Chat/coati/models/opt/__init__.py
create mode 100644 applications/Chat/coati/models/opt/opt_actor.py
create mode 100644 applications/Chat/coati/models/opt/opt_critic.py
create mode 100644 applications/Chat/coati/models/opt/opt_lm.py
create mode 100644 applications/Chat/coati/models/opt/opt_rm.py
create mode 100644 applications/Chat/coati/models/utils.py
create mode 100644 applications/Chat/coati/replay_buffer/__init__.py
create mode 100644 applications/Chat/coati/replay_buffer/base.py
create mode 100644 applications/Chat/coati/replay_buffer/naive.py
create mode 100644 applications/Chat/coati/replay_buffer/utils.py
create mode 100644 applications/Chat/coati/trainer/__init__.py
create mode 100644 applications/Chat/coati/trainer/base.py
create mode 100644 applications/Chat/coati/trainer/callbacks/__init__.py
create mode 100644 applications/Chat/coati/trainer/callbacks/base.py
create mode 100644 applications/Chat/coati/trainer/callbacks/performance_evaluator.py
create mode 100644 applications/Chat/coati/trainer/callbacks/save_checkpoint.py
create mode 100644 applications/Chat/coati/trainer/ppo.py
create mode 100644 applications/Chat/coati/trainer/rm.py
create mode 100644 applications/Chat/coati/trainer/sft.py
create mode 100644 applications/Chat/coati/trainer/strategies/__init__.py
create mode 100644 applications/Chat/coati/trainer/strategies/base.py
create mode 100644 applications/Chat/coati/trainer/strategies/colossalai.py
create mode 100644 applications/Chat/coati/trainer/strategies/ddp.py
create mode 100644 applications/Chat/coati/trainer/strategies/naive.py
create mode 100644 applications/Chat/coati/trainer/strategies/sampler.py
create mode 100644 applications/Chat/coati/trainer/utils.py
create mode 100644 applications/Chat/coati/utils/__init__.py
create mode 100644 applications/Chat/coati/utils/tokenizer_utils.py
create mode 100644 applications/Chat/examples/README.md
create mode 100644 applications/Chat/examples/inference.py
create mode 100644 applications/Chat/examples/requirements.txt
create mode 100755 applications/Chat/examples/test_ci.sh
create mode 100644 applications/Chat/examples/train_dummy.py
create mode 100755 applications/Chat/examples/train_dummy.sh
create mode 100644 applications/Chat/examples/train_prompts.py
create mode 100755 applications/Chat/examples/train_prompts.sh
create mode 100644 applications/Chat/examples/train_reward_model.py
create mode 100755 applications/Chat/examples/train_rm.sh
create mode 100644 applications/Chat/examples/train_sft.py
create mode 100755 applications/Chat/examples/train_sft.sh
create mode 100644 applications/Chat/inference/README.md
create mode 100644 applications/Chat/inference/benchmark.py
create mode 100644 applications/Chat/inference/llama_gptq/__init__.py
create mode 100644 applications/Chat/inference/llama_gptq/loader.py
create mode 100644 applications/Chat/inference/llama_gptq/model_utils.py
create mode 100644 applications/Chat/inference/llama_gptq/quant.py
create mode 100644 applications/Chat/inference/locustfile.py
create mode 100644 applications/Chat/inference/requirements.txt
create mode 100644 applications/Chat/inference/server.py
create mode 100644 applications/Chat/inference/tests/test_chat_prompt.py
create mode 100644 applications/Chat/inference/utils.py
create mode 100644 applications/Chat/pytest.ini
create mode 100644 applications/Chat/requirements-test.txt
create mode 100644 applications/Chat/requirements.txt
create mode 100644 applications/Chat/setup.py
create mode 100644 applications/Chat/tests/__init__.py
create mode 100644 applications/Chat/tests/test_checkpoint.py
create mode 100644 applications/Chat/tests/test_data.py
create mode 100644 applications/Chat/version.txt
diff --git a/applications/Chat/.gitignore b/applications/Chat/.gitignore
new file mode 100644
index 000000000..1ec5f53a8
--- /dev/null
+++ b/applications/Chat/.gitignore
@@ -0,0 +1,146 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+# Usually these files are written by a python script from a template
+# before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+docs/.build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# pipenv
+# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+# However, in case of collaboration, if having platform-specific dependencies or dependencies
+# having no cross-platform support, pipenv may install dependencies that don't work, or not
+# install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# IDE
+.idea/
+.vscode/
+
+# macos
+*.DS_Store
+#data/
+
+docs/.build
+
+# pytorch checkpoint
+*.pt
+
+# wandb log
+example/wandb/
diff --git a/applications/Chat/LICENSE b/applications/Chat/LICENSE
new file mode 100644
index 000000000..0528c89ea
--- /dev/null
+++ b/applications/Chat/LICENSE
@@ -0,0 +1,202 @@
+Copyright 2021- HPC-AI Technology Inc. All rights reserved.
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+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
diff --git a/applications/Chat/README.md b/applications/Chat/README.md
new file mode 100644
index 000000000..731005ab2
--- /dev/null
+++ b/applications/Chat/README.md
@@ -0,0 +1,269 @@
+
+ Coati - ColossalAI Talking Intelligence
+ 
+
+
+
+## Table of Contents
+
+- [Table of Contents](#table-of-contents)
+- [What is Coati ?](#what-is-coati-)
+- [Online demo](#online-demo)
+- [Install](#install)
+ - [Install the environment](#install-the-environment)
+ - [Install the Transformers](#install-the-transformers)
+- [How to use?](#how-to-use)
+ - [Supervised datasets collection](#supervised-datasets-collection)
+ - [Stage1 - Supervised instructs tuning](#stage1---supervised-instructs-tuning)
+ - [Stage2 - Training reward model](#stage2---training-reward-model)
+ - [Stage3 - Training model with reinforcement learning by human feedback](#stage3---training-model-with-reinforcement-learning-by-human-feedback)
+- [Coati7B examples](#coati7b-examples)
+- [FAQ](#faq)
+ - [How to save/load checkpoint](#how-to-saveload-checkpoint)
+- [The Plan](#the-plan)
+ - [Real-time progress](#real-time-progress)
+- [Invitation to open-source contribution](#invitation-to-open-source-contribution)
+- [Quick Preview](#quick-preview)
+- [Authors](#authors)
+- [Citations](#citations)
+- [Licenses](#licenses)
+---
+## What is Coati ?
+
+Coati is a large language model developed by Colossal-AI, which is also a unified large language model framework that has implemented the following functions
+- Supports comprehensive large-model training acceleration capabilities for ColossalAI, without requiring knowledge of complex distributed training algorithms
+- Supervised datasets collection
+- Supervised insturcts fine-tuning
+- Training reward model
+- Reinforcement learning with human feedback
+- Quantization inference
+- Fast model deploying
+- Perfectly integration with the Hugging Face ecosystem, high degree of model customization
+
+
+More details can be found in the [blog](https://www.hpc-ai.tech/blog/colossal-ai-chatgpt).
+
+
+
+
+
+## Online demo
+You can experience the performance of Coati7B on this page.
+
+[chat.colossalai.org](https://chat.colossalai.org/)
+
+> Warning: Due to model and dataset size limitations, Coati is just a baby model, Coati7B may output incorrect information and lack the ability for multi-turn dialogue. There is still significant room for improvement.
+## Install
+
+### Install the environment
+
+```shell
+conda creat -n coati
+conda activate coati
+pip install .
+```
+
+### Install the Transformers
+Given Hugging Face hasn't officially supported the LLaMA models, We fork a branch of Transformers that can be compatible with our code
+
+```shell
+git clone https://github.com/hpcaitech/transformers
+cd transformers
+pip install .
+```
+
+## How to use?
+
+### Supervised datasets collection
+
+we colllected 104K bilingual dataset of Chinese and English, and you can find the datasets in this repo
+
+Here is how we collected the data
+
+
+
+
+### Stage1 - Supervised instructs tuning
+
+Stage1 is supervised instructs fine-tuning, which uses the datasets mentioned earlier to fine-tune the model
+
+you can run the `examples/train_sft.sh` to start a supervised instructs fine-tuning
+
+```
+torchrun --standalone --nproc_per_node=4 train_sft.py \
+ --pretrain "/path/to/LLaMa-7B/" \
+ --model 'llama' \
+ --strategy colossalai_zero2 \
+ --log_interval 10 \
+ --save_path /path/to/Coati-7B \
+ --dataset /path/to/data.json \
+ --batch_size 4 \
+ --accimulation_steps 8 \
+ --lr 2e-5 \
+ --max_datasets_size 512 \
+ --max_epochs 1 \
+```
+
+### Stage2 - Training reward model
+
+Stage2 trains a reward model, which obtains corresponding scores by manually ranking different outputs for the same prompt and supervises the training of the reward model
+
+you can run the `examples/train_rm.sh` to start a reward model training
+
+```
+torchrun --standalone --nproc_per_node=4 train_reward_model.py
+ --pretrain "/path/to/LLaMa-7B/" \
+ --model 'llama' \
+ --strategy colossalai_zero2 \
+ --loss_fn 'log_exp'\
+ --save_path 'rmstatic.pt' \
+```
+
+### Stage3 - Training model with reinforcement learning by human feedback
+
+Stage3 uses reinforcement learning algorithm, which is the most complex part of the training process:
+
+
+
+
+
+you can run the `examples/train_prompts.sh` to start training PPO with human feedback
+
+```
+torchrun --standalone --nproc_per_node=4 train_prompts.py prompts.csv \
+ --pretrain "/path/to/LLaMa-7B/" \
+ --model 'llama' \
+ --strategy colossalai_zero2
+```
+
+
+For more details, see `examples/`.
+
+We also support training reward model with true-world data. See `examples/train_reward_model.py`.
+
+## Coati7B examples
+
+
+## FAQ
+
+### How to save/load checkpoint
+
+We have integrated the Transformers save and load pipeline, allowing users to freely call Hugging Face's language models and save them in the HF format.
+
+```
+from coati.models.llama import LlamaLM
+from coati.trainer import SFTTrainer
+
+model = LlamaLM(pretrained=args.pretrain)
+tokenizer = AutoTokenizer.from_pretrained(args.pretrain)
+
+trainer = SFTTrainer(model=model,
+ strategy=strategy,
+ optim=optim,
+ train_dataloader=train_dataloader,
+ eval_dataloader=eval_dataloader,
+ batch_size=args.batch_size,
+ max_epochs=args.max_epochs,
+ accimulation_steps = args.accimulation_steps
+)
+
+trainer.fit()
+trainer.save_model(path=args.save_path, only_rank0=True, tokenizer=tokenizer)
+```
+
+## The Plan
+
+- [x] implement PPO fine-tuning
+- [x] implement training reward model
+- [x] support LoRA
+- [x] support inference
+- [x] open source the reward model weight
+- [x] support llama from [facebook](https://github.com/facebookresearch/llama)
+- [x] implement PPO-ptx fine-tuning
+- [ ] integrate with Ray
+- [ ] support more RL paradigms, like Implicit Language Q-Learning (ILQL),
+- [ ] support chain of throught by [langchain](https://github.com/hwchase17/langchain)
+
+### Real-time progress
+You will find our progress in github project broad
+
+[Coati](https://github.com/orgs/hpcaitech/projects/17/views/1)
+
+## Invitation to open-source contribution
+Referring to the successful attempts of [BLOOM](https://bigscience.huggingface.co/) and [Stable Diffusion](https://en.wikipedia.org/wiki/Stable_Diffusion), any and all developers and partners with computing powers, datasets, models are welcome to join and build the Colossal-AI community, making efforts towards the era of big AI models from the starting point of replicating ChatGPT!
+
+You may contact us or participate in the following ways:
+1. [Leaving a Star ⭐](https://github.com/hpcaitech/ColossalAI/stargazers) to show your like and support. Thanks!
+2. Posting an [issue](https://github.com/hpcaitech/ColossalAI/issues/new/choose), or submitting a PR on GitHub follow the guideline in [Contributing](https://github.com/hpcaitech/ColossalAI/blob/main/CONTRIBUTING.md).
+3. Join the Colossal-AI community on
+[Slack](https://join.slack.com/t/colossalaiworkspace/shared_invite/zt-z7b26eeb-CBp7jouvu~r0~lcFzX832w),
+and [WeChat(微信)](https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/WeChat.png "qrcode") to share your ideas.
+4. Send your official proposal to email contact@hpcaitech.com
+
+Thanks so much to all of our amazing contributors!
+
+## Quick Preview
+
+
+
+
+- Up to 7.73 times faster for single server training and 1.42 times faster for single-GPU inference
+
+
+
+
+
+- Up to 10.3x growth in model capacity on one GPU
+- A mini demo training process requires only 1.62GB of GPU memory (any consumer-grade GPU)
+
+
+
+
+
+- Increase the capacity of the fine-tuning model by up to 3.7 times on a single GPU
+- Keep in a sufficiently high running speed
+
+## Authors
+
+Coati is developed by ColossalAI Team: [Fazzie](https://fazzie-key.cool/about/index.html), [FrankLeeeee](https://github.com/FrankLeeeee), [BlueRum](https://github.com/ht-zhou), [ver217](https://github.com/ver217)
+
+The Phd student [Zangwei Zheng](https://github.com/zhengzangw) and [Xue Fuzhao](https://github.com/XueFuzhao) also contributed a lot to this project.
+
+## Citations
+
+```bibtex
+@article{Hu2021LoRALA,
+ title = {LoRA: Low-Rank Adaptation of Large Language Models},
+ author = {Edward J. Hu and Yelong Shen and Phillip Wallis and Zeyuan Allen-Zhu and Yuanzhi Li and Shean Wang and Weizhu Chen},
+ journal = {ArXiv},
+ year = {2021},
+ volume = {abs/2106.09685}
+}
+
+@article{ouyang2022training,
+ title={Training language models to follow instructions with human feedback},
+ author={Ouyang, Long and Wu, Jeff and Jiang, Xu and Almeida, Diogo and Wainwright, Carroll L and Mishkin, Pamela and Zhang, Chong and Agarwal, Sandhini and Slama, Katarina and Ray, Alex and others},
+ journal={arXiv preprint arXiv:2203.02155},
+ year={2022}
+}
+
+@article{touvron2023llama,
+ title={LLaMA: Open and Efficient Foundation Language Models},
+ author={Touvron, Hugo and Lavril, Thibaut and Izacard, Gautier and Martinet, Xavier and Lachaux, Marie-Anne and Lacroix, Timoth{\'e}e and Rozi{\`e}re, Baptiste and Goyal, Naman and Hambro, Eric and Azhar, Faisal and Rodriguez, Aurelien and Joulin, Armand and Grave, Edouard and Lample, Guillaume},
+ journal={arXiv preprint arXiv:2302.13971},
+ year={2023}
+}
+
+@misc{alpaca,
+ author = {Rohan Taori and Ishaan Gulrajani and Tianyi Zhang and Yann Dubois and Xuechen Li and Carlos Guestrin and Percy Liang and Tatsunori B. Hashimoto },
+ title = {Stanford Alpaca: An Instruction-following LLaMA model},
+ year = {2023},
+ publisher = {GitHub},
+ journal = {GitHub repository},
+ howpublished = {\url{https://github.com/tatsu-lab/stanford_alpaca}},
+}
+```
+
+## Licenses
+
+Coati is licensed under the [Apache 2.0 License](LICENSE).
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