From d32ef94ad9fdd50e101ae4b6a6e2ff567f9acf4c Mon Sep 17 00:00:00 2001 From: binmakeswell <binmakeswell@gmail.com> Date: Fri, 24 Mar 2023 13:33:35 +0800 Subject: [PATCH] [doc] fix typo (#3222) * [doc] fix typo * [doc] fix typo --- README.md | 4 ++-- applications/ChatGPT/examples/README.md | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 5ce18650f..3098d72b4 100644 --- a/README.md +++ b/README.md @@ -80,7 +80,7 @@ </li> <li><a href="#Use-Docker">Use Docker</a></li> <li><a href="#Community">Community</a></li> - <li><a href="#contributing">Contributing</a></li> + <li><a href="#Contributing">Contributing</a></li> <li><a href="#Cite-Us">Cite Us</a></li> </ul> @@ -375,7 +375,7 @@ Join the Colossal-AI community on [Forum](https://github.com/hpcaitech/ColossalA [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 suggestions, feedback, and questions with our engineering team. -## Invitation to open-source contribution +## Contributing 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! You may contact us or participate in the following ways: diff --git a/applications/ChatGPT/examples/README.md b/applications/ChatGPT/examples/README.md index 60e6d68bd..203e4b495 100644 --- a/applications/ChatGPT/examples/README.md +++ b/applications/ChatGPT/examples/README.md @@ -16,7 +16,7 @@ torchrun --standalone --nproc_per_node=2 train_reward_model.py --pretrain "faceb ``` ### Features and tricks in RM training -- We support [Anthropic/hh-rlhf](https://huggingface.co/datasets/Anthropic/hh-rlhf)and[rm-static](https://huggingface.co/datasets/Dahoas/rm-static) datasets. +- We support [Anthropic/hh-rlhf](https://huggingface.co/datasets/Anthropic/hh-rlhf) and [rm-static](https://huggingface.co/datasets/Dahoas/rm-static) datasets. - We support 2 kinds of loss_function named 'log_sig'(used by OpenAI) and 'log_exp'(used by Anthropic). - We change the loss to valid_acc and pair_dist to monitor progress during training. - We add special token to the end of the sequence to get better result.