Fine-tuning LLMs can help building custom, task specific and expert models. Read this blog to know methods, steps and process to perform fine tuning using RLHF
In discussions about why ChatGPT has captured our fascination, two common themes emerge:
1. Scale: Increasing data and computational resources.
2. User Experience (UX): Transitioning from prompt-based interactions to more natural chat interfaces.
However, there's an aspect often overlooked – the remarkable technical innovation behind the success of models like ChatGPT. One particularly ingenious concept is Reinforcement Learning from Human Feedback (RLHF), which combines reinforcement learni
Building and Curating Datasets for RLHF and LLM Fine-tuning // Daniel Vila Suero // LLMs in Prod Con
Understanding LLM Fine-Tuning: Tailoring Large Language Models to Your Unique Requirements
Supervised Fine-tuning: customizing LLMs, by Jose J. Martinez, MantisNLP
Complete Guide On Fine-Tuning LLMs using RLHF
Guide to RLHF LLMs in 2024: Benefits & Top Vendors
A High-level Overview of Large Language Models - Borealis AI
Guide to Fine-Tuning Techniques for LLMs
fine-tuning of large language models - Labellerr
Reinforcement Learning from Human Feedback (RLHF)
