代码链接:GitHub - huggingface/trl 官方文档:TRL - Transformer Reinforcement Learning 功能 高效与可扩展:TRL 库使用accelerate作为核心支撑,可以从单GPU扩展到大规模多节点集群,支持DDP和DeepSpeed等方法。 PEFT集成:完全集成了 PEFT,允许在适度的硬件上使用量化和如 LoRA 或 QLoRA 等方法训练最大的模型。 unsloth ...
It is used for our survey paperTransformers in Reinforcement Learning: A Survey If you use it, please cite: The list of papers are divided into multiple categories as elaborated below taking into account the use of Transformers in the field of Reinforcement Learning. ...
There has been a wide variety of work looking at improving memory in reinforcement learning agents. External memory approaches typically have a regular feedforward or recurrent policy interact with a memory database through read and write operations. Priors are induced through the design of the speci...
team has refined the algorithm, adding more and more layers of reinforcement learning to make it better at recognizing patterns and making decisions based on those patterns. In the past year and a half, the team has made significant progress in the game, winning a record-tying 13 games in ...
5. 你能解释什么是 Transfer Learning? 6. 你能给出一个例子,说明什么是 Generative Adversarial Networks(GANs)? 7. 你能解释什么是 Reinforcement Learning? 8. 你能给出一个例子,说明什么是 Neural Turing Machines(NTMs)? 9. 你能解释什么是 One-Shot Learning? 10. 你能给出一个例子,说明什么是 ...
Deep reinforcement learningTime delayDeterministic delayed Markov Decision ProcessOffline reinforcement learningDecision transformerThe presence of observation and action delays in remote control scenarios significantly challenges the decision-making of agents that depend on immediate interactions, particularly within...
Decision Transformer 模型提出于Decision Transformer: Reinforcement Learning via Sequence Modeling 作者为 Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch。 该论文的摘要如下: 我们引入了一个将强化学习(RL)抽象为序列建模问题...
Harnessing the transformer's ability to process long time horizons of information could provide a similar performance boost in partially observable reinforcement learning (RL) domains, but the large-scale transformers used in NLP have yet to be successfully applied to the RL setting. In this work ...
AMAGO-2: Breaking the Multi-Task Barrier inMeta-Reinforcement Learning with TransformersJake Grigsby Justin Sasek † Samyak Parajuli † Daniel Adebi † Amy Zhang Yuke ZhuThe University of Texas at Austin† Equal contribution{grigsby,yukez}@cs.utexas.eduAbstractLanguage models trained on diver...
自然语言生成 (即文本生成) 是自然语言处理 (NLP) 的核心任务之一。本文将介绍神经网络文本生成领域当前最先进的解码方法 对比搜索 (Contrastive Search)。提...