Displaying 1 to 12 from 12 results

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

  •    Python

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.

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

  •    Python

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.

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

  •    Python

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.

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

  •    Python

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.




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

  •    Python

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.


DeepRL

  •    Python

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

pytorch-sentiment-neuron

  •    Python

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

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

  •    Python

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.

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

  •    Python

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.