🧬 Fine-Tuning Large Language and Protein Models on a single T4 GPU via Distillation, Quantization and Low-Rank Adaptation to run inference on proteins functions.

Fine-tuning a pre-trained BERT Model (ProtBert) in PyTorch using DeepLoc Dataset

AI platform for therapeutic peptide prediction using ProtBERT+CNN-LSTM models. Achieves 96.8% accuracy with 156K+ sequences, full-stack web interface, and 15 therapeutic categories. Production-ready Flask API + React frontend.

A pipeline for the analysis of Bert self-attention mechanism applied to proteins.

A fine-tuned ProtBert model designed for the prediction of anti-diabetic peptides from primary amino acid sequences.

Fusion model of ProtBERT and ESM-2 for cell-penetrating peptide prediction (Reproduction of FusPB-ESM2, Comp. Biol. Chem., 2024)