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  - biology
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  - code
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  - medical
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+ ---
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+ # **TinyDNABERT**
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+ ## 🌟 Overview
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+ **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.
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+ 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.
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+ 🚀 **Key Features:**
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+ - **Compact & Efficient:** Smaller memory footprint with fast inference times.
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+ - **LoRA Fine-Tuning:** Leverage Low-Rank Adaptation for quick and effective model tuning.
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+ - **Task-Specific Adaptability:** Fine-tune the model for various DNA-related tasks with ease.