stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms

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Stable Baselines3 (SB3) is a set of reliable implementations of reinforcement learning algorithms in PyTorch. It is the next major version of Stable Baselines. You can read a detailed presentation of Stable Baselines3 in the v1.0 blog post.

machine-learning reinforcement-learning robotics pytorch toolbox openai gym reinforcement-learning-algorithms sde baselines stable-baselines sb3 gsde

rex-gym - OpenAI Gym environments for an open-source quadruped robot (SpotMicro)

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The goal of this project is to train an open-source 3D printed quadruped robot exploring Reinforcement Learning and OpenAI Gym. The aim is to let the robot learns domestic and generic tasks in the simulations and then successfully transfer the knowledge (Control Policies) on the real robot without any other manual tuning. This project is mostly inspired by the incredible works done by Boston Dynamics.

machine-learning reinforcement-learning robot robotics tensorflow openai-gym python3 artificial-intelligence inverse-kinematics openai reinforcement-learning-algorithms legged-robots quadruped robotic-arm openai-gym-environments pybullet gym-environment quadruped-robot-gaits quadruped-robot spotmicro

gpt-2-simple - Python package to easily retrain OpenAI's GPT-2 text-generating model on new texts

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A simple Python package that wraps existing model fine-tuning and generation scripts for OpenAI's GPT-2 text generation model (specifically the "small" 124M and "medium" 355M hyperparameter versions). Additionally, this package allows easier generation of text, generating to a file for easy curation, allowing for prefixes to force the text to start with a given phrase. You can use gpt-2-simple to retrain a model using a GPU for free in this Colaboratory notebook, which also demos additional features of the package.

tensorflow text-generation openai textgenrnn

spacy-transformers - 🛸 Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy

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This package provides spaCy components and architectures to use transformer models via Hugging Face's transformers in spaCy. The result is convenient access to state-of-the-art transformer architectures, such as BERT, GPT-2, XLNet, etc. This release requires spaCy v3. For the previous version of this library, see the v0.6.x branch.

nlp machine-learning natural-language-processing google pytorch spacy openai transfer-learning language-model bert natural-language-understanding spacy-pipeline spacy-extension pytorch-model gpt-2 huggingface xlnet

pytorch-openai-transformer-lm - A PyTorch implementation of OpenAI's finetuned transformer language model with a script to import the weights pre-trained by OpenAI

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This is a PyTorch implementation of the TensorFlow code provided with OpenAI's paper "Improving Language Understanding by Generative Pre-Training" by Alec Radford, Karthik Narasimhan, Tim Salimans and Ilya Sutskever. This implementation comprises a script to load in the PyTorch model the weights pre-trained by the authors with the TensorFlow implementation.

neural-networks pytorch openai language-model transformer

Evolutionary-Algorithm - Evolutionary Algorithm using Python

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In these tutorials, we will demonstrate and visualize algorithms like Genetic Algorithm, Evolution Strategy, NEAT etc. All methods mentioned below have their video and text tutorial in Chinese. Visit 莫烦 Python for more.

evolutionary-algorithm genetic-algorithm neuroevolution microbial-genetic-algorithm travel-sale-problem evolution-strategy es reinforcement-learning neural-network microbial-ga neat neural-nets travel-sales-problem nes evolution-strategies openai distributed-es machine-learning tutorial

openai_lab - An experimentation framework for Reinforcement Learning using OpenAI Gym, Tensorflow, and Keras

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NOTICE: Please use the next version, SLM-Lab. An experimentation framework for Reinforcement Learning using OpenAI Gym, Tensorflow, and Keras.

keras tensorflow openai experiment policy-gradient actor-critic ddpg deep-reinforcement-learning reinforcement-learning gym lab reinforcement learning

rl-baselines3-zoo - A collection of pre-trained RL agents using Stable Baselines3, training and hyperparameter optimization included

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RL Baselines3 Zoo is a training framework for Reinforcement Learning (RL), using Stable Baselines3. It provides scripts for training, evaluating agents, tuning hyperparameters, plotting results and recording videos.

reinforcement-learning robotics optimization lab openai gym hyperparameter-optimization rl sde hyperparameter-tuning hyperparameter-search pybullet stable-baselines pybullet-environments tuning-hyperparameters

DeepRL

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This repository provides source code, links and other learning materials related to Artificial Intelligence, especially focused on Deep Reinforcement Learning.

deep-reinforcement-learning reinforcement-learning openai

pytorch-sentiment-neuron

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Click on release to get model file mlstm_ns.pt or numpy weights.

pytorch nlp-machine-learning openai rnn sentiment-analysis

gym-electric-motor - Gym Electric Motor (GEM): An OpenAI Gym Environment for Electric Motors

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The gym-electric-motor (GEM) package is a Python toolbox for the simulation and control of various electric motors. It is built upon OpenAI Gym Environments, and, therefore, can be used for both, classical control simulation and reinforcement learning experiments. It allows you to construct a typical drive train with the usual building blocks, i.e. supply voltages, converters, electric motors and load models, and obtain not only a closed-loop simulation of this physical structure, but also a rich interface for plugging in any decision making algorithm, from PI-controllers to Deep Deterministic Policy Gradient agents.

benchmark reinforcement-learning openai-gym openai converters machinelearning pmsm electrical-engineering openai-gym-environments gym-environment electric-drive motor-models

Deep-Reinforcement-Learning-for-Stock-Trading-DDPG-Algorithm-NIPS-2018 - Practical Deep Reinforcement Learning Approach for Stock Trading

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The master branch supports Tensorflow from version 1.4 to 1.14. For Tensorflow 2.0 support, please use tf2 branch. Refer to TensorFlow installation guide for more details.

deep-reinforcement-learning openai stock-trading