รู้จักกับ Local LLM และการใช้งานผ่าน Ollama API

This week, we'll explore the world of Local LLM, how to use language models on your own machine, and what they're used for. Let's learn more about them in this topic. In this topic, we'll discuss the following topics: 1. Introduction to LLM, Instruct LLM, and LLM + API. 2. Introduction to Hugging Face and LM Studio (for experimenting with prompts and LLMs in Hugging Face). 3. Introduction to Ollama and experimenting with Local LLM via the Ollama API. 4. Using Local LLM for Programming, such as Aider + Ollama. (This topic continues from the "AI for Programming" section, but with a Local LLM version.) I hope this topic helps provide a better understanding for those who are learning more about LLM and its applications. 😁 You can read more in this article. https://mikelopster.dev/posts/llm-loc... Topic 00:00 Topic Introduction 01:30 Understanding the Relationship between AI Applications and LLM 05:22 Relationship between LLM and API 08:00 Can we host LLM ourselves or fine-tune it ourselves? 11:11 What is Local LLM? 14:20 How can we connect LLM via a local API? 16:06 Introducing Hugging Face and Space 20:28 Connecting Locally Loaded LLM and Exporting it to an API 22:21 What is LM Studio? 26:57 Introducing Deepseek 27:57 Playing with LM Studio and the API 28:55 What is Ollama / Introducing the ollama command 34:25 Playing with Ollama via ollama-python 37:11 Try connecting the Ollama API to the Fast API 41:31 Using Local LLM and AI for programming 44:33 Using Aider with Ollama 47:34 Using Continue with Ollama (and adding a cursor) 52:13 Summary If you have any further questions, please feel free to discuss and exchange knowledge at: Facebook page:   / mikelopster.dev   Website: https://mikelopster.dev Here's the coordinates of what I used: https://shope.ee/6fI75UuLEM Osmo Pocket 3 https://shope.ee/4VDcVixCW9 Shure microphone https://shope.ee/6pbXI6d5xG CCTV camera Enjoy! 😘