df5e9c53cf
* Add dpo. Fix sft, ppo, lora. Refactor all * fix and tested ppo * 2 nd round refactor * add ci tests * fix ci * fix ci * fix readme, style * fix readme style * fix style, fix benchmark * reproduce benchmark result, remove useless files * rename to ColossalChat * use new image * fix ci workflow * fix ci * use local model/tokenizer for ci tests * fix ci * fix ci * fix ci * fix ci timeout * fix rm progress bar. fix ci timeout * fix ci * fix ci typo * remove 3d plugin from ci temporary * test environment * cannot save optimizer * support chat template * fix readme * fix path * test ci locally * restore build_or_pr * fix ci data path * fix benchmark * fix ci, move ci tests to 3080, disable fast tokenizer * move ci to 85 * support flash attention 2 * add all-in-one data preparation script. Fix colossal-llama2-chat chat template * add hardware requirements * move ci test data * fix save_model, add unwrap * fix missing bos * fix missing bos; support grad accumulation with gemini * fix ci * fix ci * fix ci * fix llama2 chat template config * debug sft * debug sft * fix colossalai version requirement * fix ci * add sanity check to prevent NaN loss * fix requirements * add dummy data generation script * add dummy data generation script * add dummy data generation script * add dummy data generation script * update readme * update readme * update readme and ignore * fix logger bug * support parallel_output * modify data preparation logic * fix tokenization * update lr * fix inference * run pre-commit --------- Co-authored-by: Tong Li <tong.li352711588@gmail.com> |
||
|---|---|---|
| .. | ||
| peft | ||
| ray | ||
| README.md | ||
README.md
⚠️ This content may be outdated since the major update of Colossal Chat. We will update this content soon.
Community Examples
We are thrilled to announce the latest updates to ColossalChat, an open-source solution for cloning ChatGPT with a complete RLHF (Reinforcement Learning with Human Feedback) pipeline.
As Colossal-AI undergoes major updates, we are actively maintaining ColossalChat to stay aligned with the project's progress. With the introduction of Community-driven example, we aim to create a collaborative platform for developers to contribute exotic features built on top of ColossalChat.
Community Example
Community-driven Examples is an initiative that allows users to contribute their own examples to the ColossalChat package, fostering a sense of community and making it easy for others to access and benefit from shared work. The primary goal with community-driven examples is to have a community-maintained collection of diverse and exotic functionalities built on top of the ColossalChat package, which is powered by the Colossal-AI project and its Coati module (ColossalAI Talking Intelligence).
For more information about community pipelines, please have a look at this issue.
Community Examples
Community examples consist of both inference and training examples that have been added by the community. Please have a look at the following table to get an overview of all community examples. Click on the Code Example to get a copy-and-paste ready code example that you can try out. If a community doesn't work as expected, please open an issue and ping the author on it.
| Example | Description | Code Example | Colab | Author |
|---|---|---|---|---|
| Peft | Adding Peft support for SFT and Prompts model training | Huggingface Peft | - | YY Lin |
| Train prompts on Ray | A Ray based implementation of Train prompts example | Training On Ray | - | MisterLin1995 |
| ... | ... | ... | ... | ... |
How to get involved
To join our community-driven initiative, please visit the ColossalChat GitHub repository, review the provided information, and explore the codebase. To contribute, create a new issue outlining your proposed feature or enhancement, and our team will review and provide feedback. We look forward to collaborating with you on this exciting project!