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license: isc |
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tags: |
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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. |
