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---
license: isc
tags:
- biology
- code
- medical
---
# **TinyDNABERT**
## 🌟 Overview
**TinyDNABERT** is a specialized deep learning model designed for understanding the language of DNA and performing DNA sequence classification tasks. This model is a compact and efficient version of the **DNABERT** model, optimized to reduce memory usage while maintaining high performance. TinyDNABERT is particularly well-suited for tasks where computational efficiency and fast inference times are crucial.
This repository provides all the necessary scripts and configurations to fine-tune TinyDNABERT on various DNA-related tasks using **LoRA (Low-Rank Adaptation)** configurations, enabling efficient adaptation to specific DNA sequence classification problems.
🚀 **Key Features:**
- **Compact & Efficient:** Smaller memory footprint with fast inference times.
- **LoRA Fine-Tuning:** Leverage Low-Rank Adaptation for quick and effective model tuning.
- **Task-Specific Adaptability:** Fine-tune the model for various DNA-related tasks with ease. |