FinRL is a reinforcement learning framework designed for the development, training, and backtesting of automated trading strategies. It functions as a quantitative finance toolkit that integrates deep learning algorithms with financial market simulations to address complex portfolio management and asset allocation tasks. The platform provides an end-to-end pipeline for transforming raw market data into actionable trading models. The project distinguishes itself through a layered, modular architecture that separates data processing, environment simulation, and agent training. This design allow
[X] Sample script for ORPOTrainer in 🤗 TRL is added to trl/testorpotrainerdemo.py - [X] New model, 🤗 kaist-ai/mistral-orpo-capybara-7k , is added to 🤗 ORPO Collection - [X] Now you can try ORPO in 🤗 TRL , Axolotl and LLaMA-Factory 🔥 - [X] We are making general guideline for training LLMs…
The main features of xfactlab/orpo are: Reinforcement Learning.
Open-source alternatives to xfactlab/orpo include: ai4co/rl4co. ai4finance-foundation/finrl — FinRL is a reinforcement learning framework designed for the development, training, and backtesting of automated… aikorea/awesome-rl — Reinforcement learning resources curated. airlab-polimi/mushroom. alessiodm/drl-zh — Welcome to drlzh.ai: a hands-on deep reinforcement learning course where you build the algorithms, not just read about… 2toinf/uniact — [Project Page] [Paper].
