Glossary

Instruction Tuning

What is Instruction Tuning?

Instruction tuning is a form of fine-tuning in which a pre-trained language model is trained further on many pairs of instructions and desired responses. This teaches the model to follow tasks phrased in natural language rather than merely continue text. It is a key step in turning a base model into an assistant and is often combined with methods such as RLHF. Example: 'Summarise this text in three sentences' is carried out reliably.

How KI.ordo helps

KI.ordo does not train models; it uses Anthropic's Claude models, which are already trained as assistants, and steers their behaviour through instructions and knowledge.

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Topics

Fine-tuning
Language models
Training

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Related terms

Fine-tuning

Fine-tuning means further training an already pre-trained AI model on additional, usually task-specific data. Its internal weights are adjusted so that the model handles, for instance, a particular writing style, specialist vocabulary or output format more reliably. Fine-tuning requires carefully prepared example data, computing power and testing. For many applications, well-written instructions and connected knowledge are sufficient and easier to change.

Model training
Customisation
+1

Reinforcement learning from human feedback (RLHF)

RLHF is a training method that makes language models more helpful and safer. People compare and rate several of the model's answers; these judgements are used to train a reward model, which then further trains the language model itself through reinforcement learning. This teaches it, for instance, to answer more clearly or to decline problematic requests. RLHF takes place at the model provider before a model is released – not with individual users.

training
human feedback
+1

Large language model (LLM)

A large language model (LLM) is a neural network trained on very large amounts of text, enabling it to understand and generate language. It works by calculating the most likely next token, step by step. LLMs write, summarise, translate, answer questions and generate code; well-known examples include Claude, GPT, Gemini and Llama. Without access to current sources, they only know what was in their training data.

Language models
Generative AI
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Prompt

A prompt is the input that tells an AI model what to do – a question, a task or an instruction, often supplemented with context, examples and the desired format. The quality of the answer depends heavily on how clear and complete the prompt is. For example, rather than “Write something about our product”, use “Write three short benefits of product X for trade businesses, in a factual tone”.

prompting
input
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Template