【LLM-RLHF-Tuning:用于AI训练的开源工具包,提供PPO/DPO等算法】’LLM-RLHF-Tuning - Comprehensive toolkit for Reinforcement Learning from Human Feedback (RLHF) training, featuring instruction fine-tuning, reward model training, and support for PPO and DPO algorithms with various configurations for the...
THERE ARE THREE RS IN STRAWBERRY 中间的逻辑也相对比较隐蔽:每两个字母组成一组,比如 oy 在一起,取字母表顺序的均值,'o' (15) + 'y' (25) = 40,40 再除以 2 得到 20,对应字母 t。以此类推,可以解码出来对应的内容。o1 是怎么实现这样的能力呢,纯粹从推理态来看是 inference time thinking 做到的,...
简而言之, 如果training data里的noise,在训练过程中使得某些action-values的q value过高(errors overlap),或者所有的action都是一样的q value, 会使agent没有办法学到optimal policy. 基于这篇1993年的work, 2016年的work提了为了避免overestimation, max Q value需要遵守的一个lower bound。 证明在appendix里,推...
事实上，目前像image captioning的问题前几名都是使用RL进一步提升成绩的。反过来看，简单的Seq2Seq这种直...
ModelArts是面向开发者的一站式AI开发平台,为机器学习与深度学习提供海量数据预处理及半自动化标注、大规模分布式Training、自动化模型生成,及端-边-云模型按需部署能力,帮助用户快速创建和部署模型,管理全周期AI工作流。 ModelArts:support.huaweicloud.com MLStudio:support.huaweicloud.com BML 全功能AI开发平台BML...
OpenAI universe- A software platform for measuring and training an AI's general intelligence across the world's supply of games, websites and other applications DeepMind Lab- A customisable 3D platform for agent-based AI research Project Malmo- A platform for Artificial Intelligence experimentation an...
The goal of an RL algorithm is to optimize a policy to yield maximum reward. In deep reinforcement learning, the policy is represented as aneural networkwhich is continuously updated, per the reward function, during the training process. The AI agent learns from experience, much like humans do...
We have provided the crowdsourcing templates we used on mechanical turk, along with example inputs inscripts/crowdworking_templates. You might find these a helpful starting point either for evaluating your own model's generations, or for gathering training data for a learned reward function. ...
OpenAI 在今年 6 月宣布内部训练了 CriticGPT 用于 post-training,是一个 AI code verifier:CriticGPT 能够对 ChatGPT 生成的代码进行评估,识别出错误并提修改建议。其训练方式也比较直接:通过在代码中故意设置 bug 并进行详细标注,训练出能够 debug 的模型。尽管没有说明,我们相信其目标一定是给 Q-star 训练 rew...
强化学习技巧:We integrated the implementation tricks for PPO to improve the training stability, referencing Implementation Matters in Deep Policy Gradients and ppo-implementation-details. 性能优势:快 表2提供了与DSChat的性能对比,OpenRLHF大约可以提供2倍左右的加速: image-20240526185537525 详细的配置可以参考...