Applying quantum computing principles to large language models for more reliable, interpretable, and steerable systems.
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Updated
Jan 5, 2024 - Python
Applying quantum computing principles to large language models for more reliable, interpretable, and steerable systems.
Survey of preference alignment algorithms
Intelligent AI Chatbot that has the capability to learn from the user
Code for my thesis titled "Eliciting latent knowledge from language reward models" for the MPhil in Machine Learning and Machine Intelligence at the University of Cambridge
This project is based on fine-tuning LLM models (FLAN-T5) for text summarisation task using PEFT approach. All evaluation metrics being computed on ROUGE scoring and LoRA optimisation techniques being used for fine-tuning.
An alternative RLHF reward model formulation from a social choice perspective
Projects and Models built in Python leveraging PyTorch, implementing Reinforcement Learning algorithms for reward-based tasks.
This repository is dedicated to small projects and some theoretical material that I used to get into NLP and LLM in a practical and efficient way.
Library built on TextRL for easy training and usage of fine-tuned models using RLHF, a rewards model, and PPO
Applying AlphaZero Self-Play Tactics to LLaMA for Enhanced Chatbot Interaction
This project uses LLMs to generate music from text by understanding prompts, creating lyrics, determining genre, and composing melodies. It harnesses LLM capabilities to create songs based on text inputs through a multi-step approach.
A Comparison of LLM Chat Bot Implementation Methods with Travel Use Case
Improving LLM truthfulness via reporting confidence
Direct Preference Optimization of ChatGPT2 using TRL Library
Codebase and experiments of LLM(Large Language Modeling)
Summaries of papers related to the alignment problem in NLP
Researching the reinforcement learning algorithm of ChatGPT
Embark on the "Reinforcement Learning from Human Feedback" course and align Large Language Models (LLMs) with human values.
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