The LLM Landscape: Learn Chat, Reasoning & Mixture-of-Experts (MoE) Models, Run locally using ollama скачать в хорошем качестве

The LLM Landscape: Learn Chat, Reasoning & Mixture-of-Experts (MoE) Models, Run locally using ollama

Check our website for in depth content. https://geekmonks.com/llm-eng/llm-lan... LMs come in different breeds, each designed for specific purposes. To navigate this space, we need to understand the difference between Base Models, Instruction-tuned Models, and Reasoning Models, along with the split between Frontier and Open-Source approaches. What is a Base Model ? A Base Model is a raw, PreTrained model that has only learned from its training data using the next-token prediction objective. It has not been gone through special training for following instructions or having conversations. Below are the characteristics of a Base Model. More creative but less predictable Does not reliably follow instructions Requires careful prompting or examples Good for research, fine-tuning, and experimentation Not ideal for everyday users What is an Instruction/Chat Model ? An Instruction Model (also called Chat Model or Instruct Model) is a base model fine-tuned to follow instructions, answer questions, and behave like an assistant. These models has undergo: Supervised Fine-Tuning (SFT): In this approach LLM Engineers write example instructions + ideal responses, used for training LLMs. RLHF (Reinforcement Learning with Human Feedback): In RLHF we observe and rank the responses from model and it learns from our feedback, that what “good behavior” looks like. #llm #llms #aimodel #reasoning #chatgpt #computer #education #computerscience