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xysheng-colossal 84723e8bed [feat][merge] Support one-behind to reduce bubble time. Add profiling code. (#6355) 
* [feat][merge] Support one-behind to reduce bubble time. Add profiling code.

* [feat] Update sync model by tensor, fix tMbs problem, add qwen train benchmark.

* [feat] Update consumer init to run 32B , update qwen benchmark.
2025-09-02 17:05:15 +08:00
..
Colossal-LLaMA
[Device]Support npu (#6159)
2024-12-17 15:42:39 +08:00
ColossalChat
[feat][merge] Support one-behind to reduce bubble time. Add profiling code. (#6355)
2025-09-02 17:05:15 +08:00
ColossalEval
[ColossalEval] support for vllm (#6056)
2024-09-18 17:09:45 +08:00
ColossalMoE
[MoE/ZeRO] Moe refactor with zero refactor (#5821)
2024-06-28 14:00:08 +08:00
ColossalQA
[pre-commit.ci] pre-commit autoupdate (#5572)
2024-07-01 17:16:41 +08:00
README.md
[Hotfix] README link (#5966)
2024-08-08 18:04:47 +08:00

README.md

Applications

This directory contains the applications that are powered by Colossal-AI.

The list of applications include:

  • Open-Sora: Revealing Complete Model Parameters, Training Details, and Everything for Sora-like Video Generation Models
  • ColossalChat: Replication of ChatGPT with RLHF.
  • Colossal-LLaMA: Continual Pre-training and Supervisied Fine-tuning of LLaMA2 / LLaMA3.
  • ColossalEval: Evaluation Pipeline for LLMs.
  • FastFold: Optimizing AlphaFold (Biomedicine) Training and Inference on GPU Clusters.
  • ColossalQA: Document Retrieval Conversation System
  • SwiftInfer: Breaks the Length Limit of LLM Inference for Multi-Round Conversations

Please note that the Chatbot application is migrated from the original ChatGPT folder.

You can find more example code for base models and functions in the Examples directory.