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Notebooks

A collection of jupyter and colab notebooks to practice Machine Learning and AI

  1. Summarizing Dialogies with LLMs (Colab Notebook) - a hands-on guide from a Generative AI course by DeepLearning.AI and AWS. It begins by setting up the environment, installing libraries like torch and transformers. The content then shifts to dialogue summarization, importing modules such as AutoModelForSeq2SeqLM and AutoTokenizer. A key section sources dialogues from Hugging Face's "knkarthick/dialogsum" dataset, demonstrating practical applications of Large Language Models (LLMs) in summarizing dialogues.
  2. Fine Tuning Generative AI Model for Dialogue Summarization (Colab Notebook) - The main focus of the notebook is to fine-tune a generative AI model specifically for dialogue summarization. It uses the "dialogsum" dataset from Hugging Face and employs various machine learning libraries and techniques. The notebook guides the reader through data preprocessing, model configuration, training, evaluation, and inference. It also includes Redito's comments to clarify specific steps or concepts.

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