Sep 28, 2024 · We propose HybridFlow, which combines single-controller and multi-controller paradigms in a hybrid manner to enable flexible representation and ...
Sep 28, 2024 · We propose a hybrid programming model that allows users to easily build RLHF dataflow in a few lines of code by encapsulating distributed ...
Abstract. Reinforcement Learning from Human Feedback (RLHF) is widely used in Large Language Model (LLM) alignment. Tra- ditional RL can be modeled as a ...
View recent discussion. Abstract: Reinforcement Learning from Human Feedback (RLHF) is widely used in Large Language Model (LLM) alignment.
Oct 3, 2024 · We propose HybridFlow, which combines single-controller and multi-controller paradigms in a hybrid manner to enable flexible representation and ...
Oct 31, 2024 · Our code is released now: https://lnkd.in/gKWZK3Jg Besides RLHF, we also provide examples of LLM reasoning tasks, such as Math & Code.
Oct 2, 2024 · The key idea behind HybridFlow is to combine several machine learning approaches - supervised learning, reinforcement learning, and reward ...
Nov 1, 2024 · Flexible support for various RLHF algorithms and models: HybridFlow offers modular APIs, allowing users to easily implement and extend various ...
The idea of RLHF is to use methods from reinforcement learning to directly optimize a language model with human feedback. RLHF has enabled language models ...
HybridFlow: A Flexible and Efficient RLHF Framework ... Traditional RL can be modeled as a dataflow, where each node represents computation of a neural network ( ...