A collection of Digital Signal Processing notebooks with a wireless communications theme.
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Updated
Jan 24, 2023 - Jupyter Notebook
A collection of Digital Signal Processing notebooks with a wireless communications theme.
Wii/GC texture encoder with palette support (png, jpeg, gif, bmp, tiff, tpl, tex0, plt0, bti)
On the Effects of Quantisation on Model Uncertainty in Bayesian Neural Networks
My Tensorflow Notebook. In this notebooks I have implemented various kind of model optimisation techniques.
Applying SDLC for JPEG compression project
LoRA fine-tuning and serving for NVIDIA Nemotron-3 NVFP4 MoE models on a single NVIDIA DGX Spark (GB10, 128 GB UMA)
JPEG Encoding with Discrete Cosine Transform, Quantisation & Run-Length Compression
Image compression codec based on JPEG implemented in python
Transcribe meeting audio and summarises.
A research based project to optimize the graph coloring problem using the quantisation part of image compression and come up with a solution which is better than conventional algorithms for graph coloring.
Source code: C++, SFML, MATLAB. The aim of the project was to implement various quantization algorithms in C ++ and to compare them in terms of the quality of the obtained results and the time needed to perform the calculations. On the way I've created an app with very basic GUI.
Experiments in quantisation consisting of quantisation from scratch, bitsandbytes, and llama.cpp. [Assignment 4 of Advanced Natural Language Processing, IIIT-H Monsoon '24]
Simple dithering library in Rust, based on image-rs
Optimising train, inference and throughput of expensive ML models
Pytorch implementation of Self Attention Enhanced Post Training Quantisation for Diffusion Models
A complete pipeline for deep learning model optimization via teacher fine-tuning, knowledge distillation, and 4-bit quantization. Built with PyTorch, Transformers, and BitsAndBytes.
Distributed GPT-2 fine-tuning with PyTorch FSDP and BF16 mixed precision, INT8 post-training quantisation, a custom Triton quantisation kernel achieving 1.4x throughput over unfused PyTorch, and a full FP32 vs BF16 vs INT8 benchmark suite. 13 tests passing.
A friendly CLI tool for converting and uploading transformers for CTranslate2.
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