A reference from Weave

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Build a practical understanding of language models, prompts, tokens, and context. Focus on the concepts that affect real applications and engineering workflows.

Terms beginning with L

7 terms

  • Language-model objective

    Language-model objective is a language-model concept about mechanism and information flow. It names a mechanism, representation, training practice, or operational behavior that can change how an AI system processes input and produces output.

    LLM fundamentals

  • Latent representation

    Latent representation is a language-model concept about generation behavior and sampling. It names a mechanism, representation, prompting pattern, decoding control, or context behavior that can change how an AI system processes input and produces output.

    LLM fundamentals

  • Layer normalization

    Layer normalization is a language-model concept about evaluation design and failure analysis. It names a mechanism, representation, training practice, or operational behavior that can change how an AI system processes input and produces output.

    LLM fundamentals

  • Learning rate schedule

    Learning rate schedule is a language-model concept about evaluation design and failure analysis. It names a mechanism, representation, training practice, or operational behavior that can change how an AI system processes input and produces output.

    LLM fundamentals

  • Length penalty

    Length penalty is a language-model concept about representation and similarity. It names a mechanism, representation, prompting pattern, decoding control, or context behavior that can change how an AI system processes input and produces output.

    LLM fundamentals

  • LLM inference

    LLM inference is the process of running a trained language model on an input to produce an output. For a text-generating model, it typically involves processing the input context and generating additional tokens according to a decoding strategy.

    LLM fundamentals

  • Logit lens

    Logit lens is a language-model concept about mechanism and information flow. It names a mechanism, representation, training practice, or operational behavior that can change how an AI system processes input and produces output.

    LLM fundamentals