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      • Attention is all you need
      • Emergent Abilities of Large Language Models
      • Flash Attention
      • GPT-1 Improving language understanding by Generative Pre-Training
      • gpt2 language models are unsupervised multitask learners
      • gpt3 Language Models are Few-Shot Learners
      • Griffin Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models
      • It's not just size that matters - small models are also few shot learners
      • Leave No Context Behind Efficient Infinite Context Transformers with Infini-attention
      • What we learned from a year of building with llms
      • Why Can GPT Learn In-Context
        • Analyse data
        • Create Charts
        • Import data into pandas
        • Writeup recommendations
        • Mark LLM
        • Run Different LLMS
        • Specify Marking Criteria
        • Generalise
        • LangChain
        • Read User Stories
        • Review LLM Output
        • Tune LLM
        • Create Data Transformer
        • Retrieve Database
        • Tune Data Transformer
        • Data Transformation Design
        • Specification Generator Design
        • Top Level Design Research
        • Top Level Diagram
        • Docker Image
        • LangChain
        • Notebooks
        • Ollama install
        • Pandas and Seaborn
        • Server OS Install
        • Bi Weekly tutor Updates
        • Tutorials
        • Analyse literature
        • Complete a literature search
        • Complete review of literature
        • Technical Documentation
        • Blog Setup
        • Initial Ideas
        • Lifecycle Selection
        • Log Book
        • Project Proposal
        • Project Schedule
        • Resources and Skills
        • Risk Register
        • Write Assignment
        • legal social ethical
        • reflection
        • risk assessment
        • Write Report
      • Reports
      • Tasks
      • 2024-01-14 Project Ideas
      • 2024-02-04 Environment Setup
      • 2024-02-07 Initial Project Ideas Form
      • 2024-02-13 TMA01 Planning
      • 2024-02-21 and -02-26 - TMA01 Execution
      • 2024-02-27 - TMA01 Completion
      • 2024-03-04 and 2024-03-11
      • 2024-03-18 - Testing limits of LLM's locally
      • 2024-03-27 - TMA Feedback and Reading
      • 2024-04-05 and 2024-04-10 - TMA02 and StoryTransformer
      • 2024-04-21 - TMA02 Writing
      • 2024-05-01 - TMA02 Completion
      • 2024-05-09 - StoryWeaver Initial Development
      • 2024-05-18 - StoryWeaver prompt generation and file formats
      • 2024-05-23 - Story Weaver AI
      • 2024-05-30 - TMA02 Feedback
      • 2024-06-15 - TMA03 Planning
      • 2024-06-26 - TMA03 Writing
      • 2024-07-05 - TMA03 Writing
      • 2024-07-08 - TMA03 Writing
      • 2024-07-17 - New Models and Heading Generation
      • 2024-07-24 2024-07-31 - Long Context Models - Model Comparisons
      • 2024-08-09 - Header Generation - Single Story Pass and quantitively evaluate
      • 2024-08-13 - StoryWeaver Cleanup
      • 2024-08-21 - StoryWeaver Cleanup and Diagramming
      • Final Headings
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    TMA01

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    Lifecycle Selection

    Lifecycle Selection

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    • 2024-02-21 and -02-26 - TMA01 Execution

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