Stars
Generate comic panels using a LLM + SDXL. Powered by Hugging Face 🤗
Awesome Machine Unlearning (A Survey of Machine Unlearning)
[EMNLP 2021] SimCSE: Simple Contrastive Learning of Sentence Embeddings https://arxiv.org/abs/2104.08821
Code for Paper: “Low-Resource” Text Classification: A Parameter-Free Classification Method with Compressors
Deep learning software for colorizing black and white images with a few clicks.
Code and data for paper "Deep Photo Style Transfer": https://arxiv.org/abs/1703.07511
[ICLR 2024] Fine-tuning LLaMA to follow Instructions within 1 Hour and 1.2M Parameters
OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.
[TACL'23] VSR: A probing benchmark for spatial undersranding of vision-language models.
State-of-the-Art Text Embeddings
A minimal implementation of diffusion models for text generation
[ICCV2023 Best Paper Finalist] PyTorch implementation of DiffusionDet (https://arxiv.org/abs/2211.09788)
Heterogenous, Task- and Domain-Specific Benchmark for Unsupervised Sentence Embeddings used in the TSDAE paper: https://arxiv.org/abs/2104.06979.
A collection of resources and papers on Diffusion Models
Official implementation of Diffusion Autoencoders
Self-contained, minimalistic implementation of diffusion models with Pytorch.
Utilities for creating generative artwork with Clojure
Visual experiments exploring space colonization as a 2D morphogenesis tool.
The Stream-51 dataset for streaming classification and novelty detection from videos.
Awesome Incremental Learning
Official Code of Paper HoMM: Higher-order Moment Matching for Unsupervised Domain Adaptation (AAAI2020)
PyTorch implementation of a VAE-based generative classifier, as well as other class-incremental learning methods that do not store data (DGR, BI-R, EWC, SI, CWR, CWR+, AR1, the "labels trick", SLDA).
Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.
A PyTorch implementation of center loss on MNIST
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
Cracking the Coding Interview 6th Ed. Python Solutions
Everything you need to prepare for your technical interview
Python generator for voxel data augmentation