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Mind-uploading

This project combines computing technology with personal natural language datasets such as emails, text messages, diary entries, and voice recordings.

Below are Python Notebooks for:

  • exporting datasets from native application formats (e.g., Gmail mbox, Android SMS xml) into stable forms (e.g., txt files) that may outlive the application and allow further processing
  • basic data mining and processing by large language models to identify recurring topics and communication patterns
  • tuning large language models to these datasets
  • prompting language models for personality and autobiographical information

Dataset extraction

  • Description: A Python Notebook for exporting Gmail Mbox files and converting them to TXT and JSON formats.
  • Description: A Python Notebook for converting SMS XML files to TXT, CSV, and JSON formats.
  • Description: A Python Notebook for transcribing audio files and filtering audio and transcripts for specific content.

Data Mining and Labeling

  • Description: A Python Notebook for labeling SMS (Short Message Service) conversations with OpenAI's API.
  • Description: A Python Notebook for labeling journal entries with OpenAI's API.

Tuning Large Language Models with OpenAI's API

  • Description: A Python Notebook for fine-tuning a GPT-3.5 Turbo model with OpenAI's API using the role-based system/user/assistant format.
  • Description: A Python Notebook implementing conversations with a fine-tuned GPT-3.5 Turbo model.

Prompts for Personality Trait Evaluation and Autobiographical Recall

  • Description: A Python Notebook for conducting a questionnaire related to the 16 Personality Factors model on a Large Language Model.
  • Description: A Python Notebook containing prompts for autobiographical writing.

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