Pinned Repositories
edward
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
chainer
A flexible framework of neural networks for deep learning
chainermn
ChainerMN: Scalable distributed deep learning with Chainer
keras
Deep Learning for humans
docker
Dockerfile for chainer, tf, keras, pytorch, etc..
PAE
Plummer Autoencoders
DeepSpeed
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
oh-distro
An integrated humanoid control, planning and perception system. Developed by MIT and the University of Edinburgh for the Boston Dynamics Atlas and the NASA Valkyrie humanoid robots
MannyKayy's Repositories
MannyKayy/adversarialGAN
Adversarial Learning of Robust and Safe Controllers for Cyber-Physical Systems
MannyKayy/PlayableVideoGeneration
Official Pytorch implementation of "Playable Video Generation"
MannyKayy/pytorch-pfn-extras
Supplementary components to accelerate research and development in PyTorch
MannyKayy/tape
Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.
MannyKayy/Ultra-Data-Efficient-GAN-Training
[Preprint] "Ultra-Data-Efficient GAN Training: Drawing A Lottery Ticket First, Then Training It Toughly", Tianlong Chen, Yu Cheng, Zhe Gan, Jingjing Liu, Zhangyang Wang
MannyKayy/bookcorpus
Crawl BookCorpus
MannyKayy/chatgpt-chrome-extension
A ChatGPT Chrome extension. Integrates ChatGPT into every text box on the internet.
MannyKayy/cudipy
cupy-accelerated
MannyKayy/cupyimg
CuPy implementations of image and signal processing functions from NumPy, SciPy and scikit-image
MannyKayy/differentiable-robot-model
We are implementing differentiable models of robot manipulators, which allows us to learn typically assumed to be known models of robots for control and motion planning. These models can then be used in more complex reinforcement learning settings, hopefully making learning more sample-efficient. Furthermore, such differentiable models can also be used for learning simulators.
MannyKayy/dissect
Code for the Proceedings of the National Academy of Sciences 2020 article, "Understanding the Role of Individual Units in a Deep Neural Network"
MannyKayy/fast-transformers
Pytorch library for fast transformer implementations
MannyKayy/FlexFlow
A distributed deep learning framework.
MannyKayy/GON
Gradient Origin Networks - a new type of generative model that is able to quickly learn a latent representation without an encoder
MannyKayy/google-research
Google Research
MannyKayy/gpt_index
An index created by GPT to organize external information and answer queries!
MannyKayy/LST
PyTorch Implementation for Locality Sensitive Teaching
MannyKayy/PerceptualSimilarity
MannyKayy/petals
🌸 Run 100B+ language models at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
MannyKayy/Real-Time-Voice-Cloning
Clone a voice in 5 seconds to generate arbitrary speech in real-time
MannyKayy/rwkv-cpp-cuda
A torchless, c++ rwkv implementation using 8bit quantization, written in cuda
MannyKayy/RWKV-LM
RWKV is a RNN with transformer-level performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.
MannyKayy/rwkv.cpp
INT4 and FP16 inference on CPU for RWKV language model
MannyKayy/SAM
Self-attentive Associative Memory & SAM-based Two-Memory Model
MannyKayy/sputnik
A library of GPU kernels for sparse matrix operations.
MannyKayy/torchph
The essence of my research, distilled for reusability. Enjoy 🥃!
MannyKayy/vdvae
Repository for the paper "Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images"
MannyKayy/wann-gradient-based
Gradient-Descent based search for Weight-Agnostic Neural Networks
MannyKayy/whisper
MannyKayy/xtreme-distil-transformers
XtremeDistil framework for distilling/compressing massive multilingual neural network models to tiny and efficient models for AI at scale