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Learner Reviews & Feedback for Reinforcement Learning from Human Feedback by DeepLearning.AI
About the Course
Large language models (LLMs) are trained on human-generated text, but additional methods are needed to align an LLM with human values and preferences.
Reinforcement Learning from Human Feedback (RLHF) is currently the main method for aligning LLMs with human values and preferences. RLHF is also used for further tuning a base LLM to align with values and preferences that are specific to your use case.
In this course, you will gain a conceptual understanding of the RLHF training process, and then practice applying RLHF to tune an LLM. You will:
1. Explore the two datasets that are used in RLHF training: the “preference” and “prompt” datasets.
2. Use the open source Google Cloud Pipeline Components Library, to fine-tune the Llama 2 model with RLHF.
3. Assess the tuned LLM against the original base model by comparing loss curves and using the “Side-by-Side (SxS)” method.
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1 - 3 of 3 Reviews for Reinforcement Learning from Human Feedback
By Fady A S
•Dec 12, 2024
The content is amazing, the instructor is great and the flow is well structured. I did learn a lot, however, I wish the notebooks were structured so that I can write some of the code on my own as opposed to everything being ready and already verified working.
By Manideep R E
•Jan 12, 2025
Overall worth a shot. Not in depth but good overview
By Alessandro V
•Aug 28, 2024
andrew is always a guarantor