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@ -1,6 +1,6 @@
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<h1 align="center"> |
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<span>Coati - ColossalAI Talking Intelligence</span> |
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<img width="auto" height="50px", src="assets/logo_coati.png"/> |
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<img width="auto" height="50px", src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/applications/chat/logo_coati.png"/> |
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</h1> |
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@ -60,7 +60,7 @@ You can experience the performance of Coati7B on this page.
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### Install the environment |
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```shell |
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conda creat -n coati |
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conda create -n coati |
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conda activate coati |
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pip install . |
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``` |
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@ -83,7 +83,7 @@ we colllected 104K bilingual dataset of Chinese and English, and you can find th
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Here is how we collected the data |
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<p align="center"> |
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<img src="assets/data-collect.png" width=500/> |
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<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/applications/chat/data-collect.png" width=500/> |
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</p> |
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### Stage1 - Supervised instructs tuning |
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@ -127,7 +127,7 @@ torchrun --standalone --nproc_per_node=4 train_reward_model.py
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Stage3 uses reinforcement learning algorithm, which is the most complex part of the training process: |
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<p align="center"> |
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<img src="assets/stage-3.jpeg" width=500/> |
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<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/applications/chat/stage-3.jpeg" width=500/> |
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</p> |
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you can run the `examples/train_prompts.sh` to start training PPO with human feedback |
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@ -150,67 +150,67 @@ We also support training reward model with true-world data. See `examples/train_
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<details><summary><b>E-mail</b></summary> |
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![phd](assets/Phd.png) |
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![phd](https://raw.githubusercontent.com/hpcaitech/public_assets/main/applications/chat/Phd.png) |
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</details> |
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<details><summary><b>coding</b></summary> |
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![sort](assets/quick_sort.png) |
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![sort](https://raw.githubusercontent.com/hpcaitech/public_assets/main/applications/chat/quick_sort.png) |
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</details> |
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<details><summary><b>regex</b></summary> |
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![regex](assets/regex.png) |
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![regex](https://raw.githubusercontent.com/hpcaitech/public_assets/main/applications/chat/regex.png) |
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</details> |
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<details><summary><b>Tex</b></summary> |
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![tex](assets/tex.png) |
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![tex](https://raw.githubusercontent.com/hpcaitech/public_assets/main/applications/chat/tex.png) |
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</details> |
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<details><summary><b>writing</b></summary> |
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![writing](assets/writing.png) |
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![writing](https://raw.githubusercontent.com/hpcaitech/public_assets/main/applications/chat/writing.png) |
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</details> |
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<details><summary><b>Table</b></summary> |
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![Table](assets/table.png) |
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![Table](https://raw.githubusercontent.com/hpcaitech/public_assets/main/applications/chat/table.png) |
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</details> |
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### Open QA |
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<details><summary><b>Game</b></summary> |
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![Game](assets/game.png) |
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![Game](https://raw.githubusercontent.com/hpcaitech/public_assets/main/applications/chat/game.png) |
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</details> |
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<details><summary><b>Travel</b></summary> |
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![Travel](assets/travel.png) |
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![Travel](https://raw.githubusercontent.com/hpcaitech/public_assets/main/applications/chat/travel.png) |
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</details> |
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<details><summary><b>Physical</b></summary> |
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![Physical](assets/Physical.png) |
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![Physical](https://raw.githubusercontent.com/hpcaitech/public_assets/main/applications/chat/Physical.png) |
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</details> |
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<details><summary><b>Chemical</b></summary> |
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![Chemical](assets/chemical.png) |
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![Chemical](https://raw.githubusercontent.com/hpcaitech/public_assets/main/applications/chat/chemical.png) |
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</details> |
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<details><summary><b>Economy</b></summary> |
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![Economy](assets/economy.png) |
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![Economy](https://raw.githubusercontent.com/hpcaitech/public_assets/main/applications/chat/economy.png) |
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</details> |
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