neural-network

Interpretable text embeddings by asking LLMs yes/no questions (NeurIPS 2024)

RATransformers 🐭- Make your transformer (like BERT, RoBERTa, GPT-2 and T5) Relation Aware!

Interpretable and efficient predictors using pre-trained language models. Scikit-learn compatible.

End-to-end pipeline for seeing how LLMs actually process your prompts. Capture attention across every layer, render heatmaps and cooking curves, compare variants with evidence — not vibes.

Implementation of a modular, high-performance, and simplistic mamba for high-speed applications

In this repository, I have developed an end to end Automatic speech recognition project. I have developed the neural network model for automatic speech recognition with PyTorch and used MLflow to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry.

Enhance your knowledge in medical research with the help of LLM and RAG.

Learning PyTorch through the D2L book. A series of notebooks for the same

Code for paper "Semantic Diversity-aware Prototype-based Learning for Unbiased Scene Graph Generation (ECCV 2024)"

Qdrant operator creates and manages Qdrant clusters running in Kubernetes

MinimalGPT is a concise, adaptable, and streamlined code framework that encompasses the essential components necessary for the construction, training, inference, and fine-tuning of the GPT model. This framework is implemented exclusively using Keras and TensorFlow, ensuring compatibility and coherence within the broader deep learning ecosystem.

Implementation for the different ML tasks on Kaggle platform with GPUs.

A Deep Learning project that uses Diffusion transformers (DiT) to generate Grand Theft Auto V driving footage

i have build speech recognition app using mozilla deepspeech

Engineered an advanced deep learning model to automate the classification of financial documents, including Balance Sheets, Cash Flow and Income Statements using Bidirectional LSTM and TensorFlow. The model achieved an impressive accuracy of 96.2%, enhancing efficiency and reducing errors in document management for the finance and banking sectors.

The open source community's implementation of the all-new Multi-Modal Causal Attention from "DeepSpeed-VisualChat: Multi-Round Multi-Image Interleave Chat via Multi-Modal Causal Attention"

A deep learning project for detecting and classifying teeth as normal or cavity using YOLOv12m. The model is integrated into a web application for real-time dental screening. Designed to enhance early diagnosis accessibility, with future improvements planned for dataset expansion, annotation quality, and robustness to real-world conditions.

Deep learning models(CNN, LSTM, BERT) for image and text classification task with Tensorflow and Keras