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---
task_categories:
- image-segmentation
license: mit
tags:
- parameter-efficient-fine-tuning
- peft
- segment-anything
- sam
- medical-image-segmentation
---
This repository contains the code for SALT: Parameter-Efficient Fine-Tuning via Singular Value Adaptation with Low-Rank Transformation. SALT is a method for adapting large-scale foundation models, particularly the Segment Anything Model (SAM), to domain-specific tasks, such as medical image segmentation, with high parameter efficiency.
Paper: [SALT: Parameter-Efficient Fine-Tuning via Singular Value Adaptation with Low-Rank Transformation](https://huggingface.co/papers/2503.16055)
Code: https://github.com/YourUsername/SALT.git
The following datasets, used in the experiments, are available on Hugging Face:
- **ROSE:** (https://huggingface.co/datasets/pythn/ROSE)
- **ARCADE:** (https://huggingface.co/datasets/pythn/ARCADE)
- **DRIVE:** (https://huggingface.co/datasets/pythn/drive)
- **DIAS:** (https://huggingface.co/datasets/pythn/DIAS)
- **Xray-Angio:** (https://huggingface.co/datasets/pythn/DB) |