Artificial Language Luminary (ALL) is an open source Large Language Model (LLM), that runs on data collected from searches on Omega Search Engine. (Beta Version)

QAYPD(Question-Answer Your Personal Documents), an AI tool to help you answer questions related to your personal documents quickly via leveraging the computational capabilities of OpenAI's GPT LLM (Large Language Model).

Experiments with Harmony

A rust voice assistant which is was made to be easy to set up, customize and learn from.

Classification of Imbalanced Data with Large Language Model (Google T5)

Deploy Large Models on AWS Inferentia (Inf2) instances.

FLARES: FINE-GRAINED LANGUAGE-BASED RELIABILITY DETECTION IN SPANISH NEWS

LangSphere is an interactive AI playground specially developed to demonstrate the capabilities of large language models (LLMs) within the realm of Augmented Analytics.

Prompt-engineered GPT3.5 for roasting users like a close friend

This is an eldritch project to resurrect the man himself using retrieval augmented generation on his letters

Question and Answer LLM Wrapper

Harnessing large language models over transformer models for detecting Bengali depressive social media text: A comprehensive study

The open-source repository llm.gallery aggregates research & development content about Large Language Models (LLMs). Explore curated academic papers, community contributions, and educational content on LLM and related topics.

Introduction to the Harmony project

A wiki about large language models.

Chat with your favorite AI Assistant directly from the comfort of your terminal.

Talk_with_PDF is a powerful, AI-driven solution designed to automate the extraction of information and generation of answers based on PDF documents. By integrating OpenAI's advanced language models and embeddings, this system provides accurate and contextually relevant responses, making it an invaluable tool for education, business, and research.

LLM-based for highly remote sensing data imputation

This project utilizes a machine learning model where consumer brand data is employed. Initially, a preliminary model is developed, followed by a refined model using a process called 'fine-tuning' to improve results. Additionally, a comprehensive testing suite has been created to validate accuracy and reliability of the model's predictions.