Proof-of-concept leveraging DPO loss to fine-tune a ResNet to classify images from CIFAR10 dataset.
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Updated
Aug 30, 2024 - Python
Proof-of-concept leveraging DPO loss to fine-tune a ResNet to classify images from CIFAR10 dataset.
DPO using human Votes, Model Combat is an application that compares responses from different AI models (ChatGPT, Hanooman, and Cohere) based on user inputs. Users can vote on which model gives a better response or remark on the responses. The results are saved in Google Sheets for further analysis.
EasyRLHF aims to provide an easy and minimal interface to train aligned language models, using off-the-shelf solutions and datasets
Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization
A open-source framework designed to adapt pre-trained Language Models (LLMs), such as Llama, Mistral, and Mixtral, to a wide array of domains and languages.
Learning to route instances for Human vs AI Feedback
Data and models for the paper "Configurable Safety Tuning of Language Models with Synthetic Preference Data"
Examples for using the SiLLM framework for training and running Large Language Models (LLMs) on Apple Silicon
🌾 OAT: Online AlignmenT for LLMs
[NeurIPS 2024] Official code of $\beta$-DPO: Direct Preference Optimization with Dynamic $\beta$
[ACL 2024] Self-Training with Direct Preference Optimization Improves Chain-of-Thought Reasoning
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