Gunale0926/SORSA

SORSA: Singular Values and Orthonormal Regularized Singular Vectors Adaptation of Large Language Models

42
/ 100
Emerging

This project helps machine learning engineers adapt large language models (LLMs) for specific tasks, like answering math problems or coding, more efficiently. It takes a pre-trained LLM and a dataset for a new task, applying a method called SORSA to fine-tune the model with fewer computational resources. The result is a fine-tuned LLM that performs well on the new task without increasing the model's size or slowing down its inference.

No commits in the last 6 months. Available on PyPI.

Use this if you need to fine-tune large language models for specific downstream tasks without the extensive computational demands or increased inference latency typically associated with full fine-tuning.

Not ideal if you are a general user looking for an off-the-shelf LLM application rather than a tool for model adaptation.

LLM fine-tuning natural-language-processing machine-learning-engineering model-adaptation computational-efficiency
Stale 6m
Maintenance 0 / 25
Adoption 7 / 25
Maturity 25 / 25
Community 10 / 25

How are scores calculated?

Stars

38

Forks

4

Language

Python

License

Apache-2.0

Last pushed

Feb 24, 2025

Commits (30d)

0

Dependencies

2

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/transformers/Gunale0926/SORSA"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.