Professor Codephreak

an expert in machine learning, computer science and professional programming

Professor Codephreak Software Engineer Machine Learning Platform Architect

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Reliable fully local RAG agents with LLaMA3

https://github.com/langchain-ai/langgraph/blob/main/examples/rag/langgraph_rag_agent_llama3_local.ipynb Building reliable local agents using LangGraph and LLaMA3-8b within the RAGE framework involves several key components and methodologies: Model Integration and Local Deployment: LLaMA3-8b: Utilize this robust language model for generating responses based on user queries. It serves as the core generative engine in the RAGE system. LangGraph: Enhance the responses of LLaMA3 by integrating structured knowledge graphs through LangGraph, boosting the model’s capability to deliver contextually relevant and accurate information. Advanced RAGE Techniques: […]

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MASTERMIND

MASTERMIND

MASTERMIND is an advanced agency control structure designed for intelligent decision-making and strategic analysis. It orchestrates the interaction between various components of a larger system, managing workflows and ensuring consistency across operations. MASTERMIND integrates modules for prediction, reasoning, logic, non-monotonic reasoning, and more to handle complex tasks dynamically and adaptively. Here are some key aspects of MASTERMIND: Modular Architecture: It coordinates between multiple modules like prediction, logic, and reasoning to process data and execute complex […]

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easyAGI: Augmenting the Intelligence of Large Language Models

easy augmented general intelligence In the rapidly evolving field of artificial intelligence, the concept of Autonomous General Intelligence (AGI) represents a significant milestone. However, the journey towards AGI is complex and requires innovative approaches to streamline and simplify the development process. Enter easyAGI, a transformative framework designed to augment the intelligence of existing Large Language Models (LLMs). This article explores the core aspects of easyAGI and its impact on the landscape of AGI and LLMs. […]

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