Final Exam: Architecting LLMs for Your Technical Solutions

Intermediate
  • 1 video | 32s
  • Includes Assessment
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Final Exam: Natural Language Processing Fundamentals will test your knowledge and application of the topics presented throughout the Natural Language Processing track.

WHAT YOU WILL LEARN

  • Introduce the hugging face platform
    recall how tokenization works for transformer models
    work with the hugging face platform
    set up a colab notebook
    train a bpe tokenizer
    perform normalization and pre-tokenization with wordpiece
    recall the use of hugging face pipelines
    perform zero-shot classification
    perform sentiment analysis
    perform sentiment analysis with finbert
    perform ner with a bert model
    perform language translation with the t5 model
    summarize text using bart and t5s
  • evaluate text summaries using rouge scores
    compute text similarity with sentence transformers
    fine-tune a bert classifier
    generate predictions with a fine-tuned model
    load and clean text for ner
    align ner tags with subword tokens
    fine-tune bert for ner
    load and process data for causal language modeling (clm)
    fine-tune a distilgpt model for clm
    fine-tune the t5-small model for translation
    summarize text with a regular t5-small model
    fine-tune a t5-small model for summarization

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