beresandras's starred repositories

CORL

High-quality single-file implementations of SOTA Offline and Offline-to-Online RL algorithms: AWAC, BC, CQL, DT, EDAC, IQL, SAC-N, TD3+BC, LB-SAC, SPOT, Cal-QL, ReBRAC

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guided-diffusion-keras

Text to Image Diffusion Models in Keras

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stable-diffusion-tensorflow

Stable Diffusion in TensorFlow / Keras

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PyTorch-StudioGAN

StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.

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keras-io

Keras documentation, hosted live at keras.io

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MarkovJunior

Probabilistic language based on pattern matching and constraint propagation, 153 examples

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cleanrl

High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

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pytorch-image-models

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

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ai-generated-pokemon-rudalle

Python script to preprocess images of all Pokémon to finetune ruDALL-E

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frog-dataset

Dataset of frogs on a white background for ML experiments

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awesome-mlss

🤖 Machine Learning Summer School deadlines

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Transformers-Recipe

🧠 A study guide to learn about Transformers

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keras

Deep Learning for humans

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solo-learn

solo-learn: a library of self-supervised methods for visual representation learning powered by Pytorch Lightning

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pytorch-lightning

Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.

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stable-baselines

A fork of OpenAI Baselines, implementations of reinforcement learning algorithms

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stable-baselines3

PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

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accelerate

🚀 A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed support

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