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Transformers and LLM Foundations

Folder: Research/Machine-Learning-and-AI/Transformers-and-LLM-Foundations

8 items under this folder.

  • Sep 23, 2026

    Transformers and LLM Foundations - Index

    • type/index
    • source/ingested
    • topic/machine-learning
    • topic/transformers
    • topic/large-language-models
  • Sep 18, 2026

    Autoregressive Language Modeling and Pretraining

    • source/ingested
    • topic/machine-learning
    • topic/large-language-models
    • topic/language-modeling
    • type/concept
    • doc/paper
  • Sep 18, 2026

    Compute-Optimal Training (Chinchilla)

    • source/ingested
    • topic/machine-learning
    • topic/large-language-models
    • topic/scaling-laws
    • topic/resource-allocation
    • type/method
    • doc/paper
  • Sep 18, 2026

    In-Context Learning and Few-Shot Prompting

    • source/ingested
    • topic/machine-learning
    • topic/large-language-models
    • topic/in-context-learning
    • topic/prompting
    • type/concept
    • doc/paper
  • Sep 18, 2026

    Neural Scaling Laws

    • source/ingested
    • topic/machine-learning
    • topic/large-language-models
    • topic/scaling-laws
    • type/concept
    • doc/paper
  • Sep 18, 2026

    Transformers and LLM Foundations - Overview

    • source/ingested
    • topic/machine-learning
    • topic/transformers
    • topic/large-language-models
    • type/overview
    • doc/paper
  • Sep 18, 2026

    Scaled Dot-Product and Multi-Head Attention

    • source/ingested
    • topic/machine-learning
    • topic/transformers
    • topic/attention
    • type/concept
    • doc/paper
  • Sep 18, 2026

    Transformer Architecture and Positional Encoding

    • source/ingested
    • topic/machine-learning
    • topic/transformers
    • topic/neural-network-architecture
    • type/concept
    • doc/paper

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  • GitHub
  • llms.txt