Universal Personal Assistant with LLMsLarge Language Models are a unique emergent technology of 2024. Its fascinating capabilities to produce coherent text influences many areas…Dec 12Dec 12
LLM Evaluation: Which LLM to use for developing a personal assistant?In my blog series, I covered several aspects of LLMs: Understanding their evolution, investigating libraries, researching, and trying how…Dec 2Dec 2
Fine-Tuning LLMs: Comparison of Collab, Kaggle and 6 other PlatformsFine-Tuning and evaluating LLMs require significant hardware resources, mostly GPUs. Building an on-premise machine learning computer is…Nov 21Nov 21
Fine Tuning LLMs: Training with Cloud ResourcesFine-Tuning LLMs with 7B or more parameters require substantial hardware resources. One option is to build and on-premise computer with…Nov 11Nov 11
LLM GUI: Custom Python Gradio InterfaceWhen using Large Language Models (LLMs) via an API or locally, a quasi-standard for representing the chat history is recognizable: A list…Oct 31Oct 31
LLM Agents: Introduction to CrewAIAgent frameworks powered by LLMs promise to catapult autonomous task solving to unprecedented levels. Instead of rigid programming, LLMs…Oct 21Oct 21
LLM Agents: Multi-Agent Chats with AutogenAn agent is a Large Language Models customized with a system prompt so that it behaves in a specific way. The prompt typically details task…Oct 10Oct 10
LLM Agents: Custom Tools in AutogenLarge Language Models used as agents promise automatic task solution and to promote LLM usage to the next level. Effectively, an agent is…Sep 30Sep 30
LLM Agents: Introduction to AutogenIn my ongoing quest to design a question-answer system, agents are the final available design. An LLM agent is an instance of an LLM with a…Sep 23Sep 23
LangChain: Building a local Chat Agent with Custom Tools and Chat HistoryThe LangChain library spearheaded agent development with LLMs. When running an LLM in a continuous loop, and providing the capability to…Sep 16Sep 16
