Reinforcement Learning from Human Feedback
Thanks for attending our session at PyData Berlin!
Check out the following resources and further references, or take a stab at Reinforcement Learning with Human Feedback yourself!
Internet-trained models bring with them internet-scaled biases.
Thanks to the power of Reinforcement Learning with Human Feedback(RLHF), we can now adjust for problems that tend to come with large-scale foundational models.
In the talk by Erin Mikail Staples and Nikolai Liubimov presented at PyData Berlin 2023, they shared not only why RLHF is a good solution to improving on existing large models but also how it works.
RHLF is currently being used in the wild in projects like OpenAI and BloombergGPT to build specific use-case-driven adaptations of large foundational models.
Keep the fun going learn more about Label Studio by checking out the following resources
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