Tag: natural language processing

Large Language Models (LLMs) are prone to generating false information, a phenomenon known as "hallucination." This analysis explores the underlying causes, from training methodologies that reward guessing over accuracy to the inherent limitations of current AI architectures. It delves into the challenges of mitigating these "lies" and questions whether a fundamental shift in LLM training and evaluation is necessary to foster true reliability.

This article explores the innovative CA-HACO-LF model, which leverages AI to enhance drug discovery by optimizing drug-target interactions. It details the model's methodology, including data preprocessing, feature extraction, and its hybrid classification approach, highlighting its superior performance over existing methods.

This tutorial demonstrates how to fine-tune a state-of-the-art summarization model using Amazon SageMaker and 🤗 Transformers with your own custom dataset. We cover the end-to-end process, from data preparation and model training to deployment and creating a simple user interface.