A client has a system that collects news artifacts from web pages, tweets, facebook posts, etc. The client is interested in scoring a given new artifact against a topic.

The client needs the news items to get scored in the range from 0 to 10; a score of 0 means the news item is totally NOT relevant while a score of 10 means the news item is very relevant.

The range of results between 0 and 10 signifies the degree of relevance of the news item to the topic.

The task is to prompt engineer GPT3-like LLMs for downstream task like news scoring and named entity extraction.

Prompt engineer Large Language Models for news scoring and Named Entity Extraction

The data used for this project can be found News scoring and named_entity

Structure of the repository -

├── models  (contains trained model)
├── .github  (github workflows for CI/CD, CML)
├── screenshots  (Important screenshots)
├── mlruns  (contains MLflow runs)
├── train (contains training scripts) 
├── assets  (contains assets)
├── data    (contains data of train, store, and test)
├── scripts (contains the main script)	
│   ├── logger.py (logger for the project)
overview)
│   ├── plot.py (handles plots)
│   ├── preprocess.py (Data preprocessing)
├── notebooks	
|   ├── api_connection.ipynb(setting up api connection with CO:here)
│   ├── eda.ipynb (overview of the Data)
│   ├── preprocess.ipynb (Preparing the data)
│   ├── model.ipynb (LLM model)
├── tests 
│   ├── test_preprocess.py (test for the the preprocess testing script)
├── README.md (contains the project description)
├── requirements.txt (contains the required packages)
|── LICENSE (license of the project)
├── setup.py (contains the setup of the project)
└── .dvc (contains the dvc configuration)

The project requires the following: python3 Pip3

Local Development

1. Activate environement or create one:

conda create -n <env-name> && conda activate <env-name>

2. Install required packages

pip install -r requirements.txt

3. Run the app

python3 wsgi.py

Henok Desalegn

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.