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Using the new open-sourced GPT Neo and horoscopes scraped and cleaned from various sources, fine-tune the model to generate realistic horoscopes on demand.

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kzhekov/GPTNeo-Horoscopes

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Horoscope generation with GPT, Transformers, Fast API and GCP

This project implements a complete cloud-hosted NLP pipeline for generating (hopefully) well-written horoscopes using Python 3 for the machine learning, data processing and API serving. It uses a variety of open source libraries such as Huggingface’s Transformers, PyTorch and FastAPI. It also has a small demo website implemented in HTML, CSS and JS that can be used to preview generated horoscopes for each of the zodiac signs. For a detailed explanation of the implementation, feel free to check out this Medium article.

This project consists in

  • Scraping horoscopes from websites known to publish horoscopes daily, and store them as a CSV for later use or use other scraped horoscopes (only data is available)
  • Using a pre-trained open-source version of GPT3 (GPTNeo) and fine-tune it to generate horoscopes when given a particular zodiac sign
  • Creating a model wrapper that would handle data pre-processing, horoscope post-processing and deliver predictions from the horoscope model
  • Creating a REST API using FastAPI that would handle prediction requests for the various zodiac signs
  • Containerizing the API and the model using Docker and host it for public predictions on the Google Cloud Platform
  • Creating a small website to test out the horoscope generation easily and scrape some rust off my web developing skills that you can check out here

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Using the new open-sourced GPT Neo and horoscopes scraped and cleaned from various sources, fine-tune the model to generate realistic horoscopes on demand.

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