Niharika Singh

In Large language models(LLM), developers and researchers face a significant challenge in accurately measuring and comparing the capabilities of different chatbot models.

Mistral.rs: A Lightning-Fast LLM Inference Platform with Device Support, Quantization, and Open-AI API Compatible HTTP Server and Python Bindings

ScrapeGraphAI: A Web Scraping Python Library that Uses LLMs to Create Scraping Pipelines for Websites, Documents, and XML Files

Fine-tuning large language models (LLMs) efficiently and effectively is a common challenge.

Latent Guard: A Machine Learning Framework Designed to Improve the Safety of Text-to-Image T2I Generative Networks

MS MARCO Web Search: A Large-Scale Information-Rich Web Dataset Featuring Millions of Real Clicked Query-Document Labels

KnowHalu: A Novel AI Approach for Detecting Hallucinations in Text Generated by Large Language Models (LLMs)

Marker: A New Python-based Library that Converts PDF to Markdown Quickly and Accurately

In the vast world of data science, countless tools are available to help analysts and researchers make sense of data and build powerful machine-learning models.

Phidata: An AI Framework for Building Autonomous Assistants with Long-Term Memory, Contextual Knowledge and the Ability to Take Actions Using Function Calling