LLM Tutorial Explains Foundation, Instruct, and Chat Model Differences

A tutorial demonstrates the distinctions between foundation, instruct, and chat models in large language models. It uses the SmolLM2-135M family, runnable on Google Colab without a GPU, to illustrate how models evolve from basic text completion to helpful assistants. The tutorial highlights that foundation models predict the next token, instruct models are fine-tuned on instruction-response pairs and require specific formatting, and chat models build upon instruct models by adding conversational memory. AI

IMPACT Clarifies the distinct capabilities and training stages of LLMs, helping users understand model behavior and limitations.

RANK_REASON The item is a tutorial explaining technical concepts related to LLM training stages, akin to an educational paper. [lever_c_demoted from research: ic=1 ai=1.0]

Read on dev.to — LLM tag →

• ChatGPT
• France
• Germany
• Google Colab
• Hugging Face
• HuggingFaceTB/SmolLM2-135M
• Italy
• SmolLM2
• SmolLM2-135M

• paper

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →