Francis LaBounty's Projects
An application to predict the price of AirBnBs
The Unit 3 & 4 build week project: Predicting AirBnB prices.
Basic ANN Framework utilizing cudnn and the CUDA programming language. Sources: "Learn CUDA programming" from Jaegeun Han and Bharatkumar Sharma.
Functional ANN framework utilizing cudnn and the CUDA programming language to create a python module. Sources: "Learn CUDA programming" from Jaegeun Han and Bharatkumar Sharma.
Code for Motion Representations for Articulated Animation paper
Asynchronous pipeline example with callbacks and event recorders to further understand teachings from the book "Learn CUDA Programming" from Jaegeun Han and Bharatkumar Sharma.
Implementation of AudioLM, a SOTA Language Modeling Approach to Audio Generation out of Google Research, in Pytorch
CPU python module for Blender 3D addon Bent Normals
CUDA python module for Blender 3D addon Bent Normals
Implementation of a blockchain miner using the CUDA language and with the help of a tutorial from youtube that I can no longer locate.
Code for the paper "Using Human Feedback to Fine-tune Diffusion Models without Any Reward Model"
ChatGPT desktop app made with PyQT5. Features include web search, prompt manager, wolfram alpha integration, pdf summarization and more!
cublas SGEMM implementation using the CUDA programming language. Asynchronous and serial versions provided. Sources: "Learn CUDA Programming" from Jaegeun Han and Bharatkumar Sharma.
An example showcasing recursion with dynamic parellelism using the CUDA programming language. Sources: "Learn CUDA Programming" from Jaegeun Han and Bharatkumar Sharma.
Implementation of parallel reduction using the CUDA programming language. Benchmarking code included to test how various memory or computation optimizations improve performance. Sources: "Learn CUDA Programming" from Jaegeun Han and Bharatkumar Sharma.
Simple SGEMM implementation using the CUDA programming language. Sources: "Learn CUDA Programming" from Jaegeun Han and Bharatkumar Sharma.
An example of how CUDA streams are created, managed, and destroyed to help understand CUDA while working through the book "Learn CUDA Programming" from Jaegeun Han and Bharatkumar Sharma.
Datasets used in Plotly examples and documentation
A repository to consolidate stable diffusion finetuning scripts. Train inpainting, depth, v1+, v2+, image variations, image colorization, whatever. Train with optimizations like 8 bit adam and xformers for faster and more memory efficient training.
adaptation of huggingface's dreambooth training script to support depth2img
Transformer related optimization, including BERT, GPT
Flappy Bird NFT to demonstrate the capabilities of the GameStop NFT wallet.