Fine-tuning a RoBERTa model for sentiment analysis on the IMDB movie reviews dataset using the Adapter method and PyTorch Transformers
An end-to-end AI-powered mobile productivity assistant that transforms natural language into reliable actions for managing tasks, meetings, notes, and progress. Built with intelligent language understanding, deterministic execution, and workflow automation for efficient productivity management.
Multilingual spellings correction and Question Answering Large Language Models
Bio-inspired adapters that improve foundation models beyond LoRA fine-tuning. 50+ neuroscience mechanisms searched via Thompson sampling over 10²² configurations. Validated on 20 benchmarks (85% win rate). Includes AI bias detection across major models.
Add a description, image, and links to the adapter-finetuning topic page so that developers can more easily learn about it.
To associate your repository with the adapter-finetuning topic, visit your repo's landing page and select "manage topics."