OPTForCasualLM Support (facebook/opt Series)#7440
OPTForCasualLM Support (facebook/opt Series)#7440b8zhong wants to merge 3 commits intosgl-project:mainfrom
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Summary of Changes
Hello @b8zhong, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!
This pull request integrates the Facebook OPT series of large language models into the system. It involves adding the complete model definition and associated components, ensuring compatibility with existing infrastructure, and updating documentation to reflect the expanded model support.
Highlights
- New Model Support: I've added comprehensive support for the Facebook OPT series of large language models, ranging from 125M to 175B parameters. This includes the full model architecture, attention mechanisms, and weight loading logic, enabling the system to efficiently run and utilize these models.
- Activation Function Registration: The
nn.ReLUactivation function has been registered in the activation registry. This is a necessary step as ReLU is used within the OPT models' architecture. - Documentation Update: The
docs/supported_models/generative_models.mdfile has been updated to officially list the OPT series as a newly supported generative model.
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Code Review
The pull request adds support for the OPT model family, including adding ReLU to the activation registry and implementing the OPT model architecture in python/sglang/srt/models/opt.py. The changes seem well-structured and include performance evaluation. A suggestion was made to improve the documentation.
Motivation
Expand support for the OPT series, this includes from
opt-125mtoopt-175b.Modifications
Add the required modelling code. Note that since the activation is ReLU I added it to the activation registry for it to work.
Evaluation (MMLU):
python3 bench_other.py --nsub 10 --backend vllmandpython3 bench_sglang.py --nsub 10onfacebook/opt-125m: