A causal language model is a model trained to predict the next word in a sequence, using only the tokens to its left (previous context). It’s unidirectional.

For example:

Input: “The weather is” → Predict: “sunny”

Popular causal LMs:

• GPT-2 / GPT-3
• Gemma
• LLaMA
• Falcon Contrast this with masked models (like BERT), which predict missing words in the middle.