Owen-Oertell's Stars
Cornell-RL/ailboost
ZhaolinGao/REBEL
twitter/the-algorithm-ml
Source code for Twitter's Recommendation Algorithm
Cornell-RL/drpo
Dateset Reset Policy Optimization
Owen-Oertell/rlcm
google-research/arxiv-latex-cleaner
arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper to submit to arXiv
nerfies/nerfies.github.io
kevinzhou497/distcb
dhruvsreenivas/jax_sandbox
JAX messaround
CarperAI/trlx
A repo for distributed training of language models with Reinforcement Learning via Human Feedback (RLHF)
Cornell-RL/tril
openai/consistency_models
Official repo for consistency models.
huggingface/diffusers
🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
python/cpython
The Python programming language
google-deepmind/rlax
google-deepmind/jaxline
kvablack/ddpo-pytorch
DDPO for finetuning diffusion models, implemented in PyTorch with LoRA support
jannerm/ddpo
Code for the paper "Training Diffusion Models with Reinforcement Learning"
openxla/xla
A machine learning compiler for GPUs, CPUs, and ML accelerators
google/paxml
Pax is a Jax-based machine learning framework for training large scale models. Pax allows for advanced and fully configurable experimentation and parallelization, and has demonstrated industry leading model flop utilization rates.
google-deepmind/optax
Optax is a gradient processing and optimization library for JAX.
google-deepmind/dm-haiku
JAX-based neural network library
gcc-mirror/gcc
microsoft/clang
llvm/llvm-project
The LLVM Project is a collection of modular and reusable compiler and toolchain technologies.
mist64/perfect6502
perfect6502, a MOS 6502 CPU emulator that performs a simulation of the original NMOS 6502 netlist
vwxyzjn/cleanrl
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
janestreet/core
Jane Street Capital's standard library overlay
ocaml/ocaml
The core OCaml system: compilers, runtime system, base libraries
facebookresearch/segment-anything
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.