Stars
A latent text-to-image diffusion model
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
A game theoretic approach to explain the output of any machine learning model.
Instruct-tune LLaMA on consumer hardware
A guidance language for controlling large language models.
StableLM: Stability AI Language Models
Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything
Zero-Shot Speech Editing and Text-to-Speech in the Wild
YOLOv6: a single-stage object detection framework dedicated to industrial applications.
Solve puzzles. Improve your pytorch.
I took Andrew Ng's Machine Learning course on Coursera and did the homework assigments... but, on my own in python because I love jupyter notebooks!
[CVPR 2024] 4D Gaussian Splatting for Real-Time Dynamic Scene Rendering
Attempting to replicate "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem" https://arxiv.org/abs/1706.10059 (and an openai gym environment)
A library for making RepE control vectors
Generative Models Tutorial with Demo: Bayesian Classifier Sampling, Variational Auto Encoder (VAE), Generative Adversial Networks (GANs), Popular GANs Architectures, Auto-Regressive Models, Importa…
FPGA-based neural network inference project with an end-to-end approach (from training to implementation to deployment)
A simple implimentation of Bayesian Flow Networks (BFN)
A resource for learning about deep learning techniques from regression to LSTM and Reinforcement Learning using financial data and the fitness functions of algorithmic trading
Linear model training using stochastic gradient descent (SGD) on PYNQ with full to low precision.
Python implementation of the PGE algorithm