A repository to explore the latest developments in LLMs and run experiments!

• Retrieval-Augmented Generation
• Synthetic Data Generation
• Model Fetcher

Retrieval-Augmented Generation

retrieval-augmented-generation.py
Experiments with a Retrieval-Augmented Generation pipeline using the LangChain and the HuggingFace frameworks.

Synthetic Data Generation

generate_synthetic_data.py
Generates artifical data from the input content prompt provided using llamafiles version of TinyLlama-1.1B model.

    Example of Input:
        name,region
        Rahul,India
        Mark,America
        Schneider,Germany
        OKenny,Ireland
        Mieke,Germany

The output that is generated is

        1. Name: Rahul
        Region: India
        2. Name: Mark
        Region: America
        3. Name: Schneider
        Region: Germany
        4. Name: OKenny
        Region: Ireland
        5. Name: Mikee
        Region: Germany
        6. Name: Miek
        Region: Germany
        7. Name: Jake
        Region: United States
        8. Name: Sarah
        Region: United Kingdom
        9. Name: John
        Region: United Kingdom
        10. Name: Tom
        Region: United Kingdom

Model Fetcher

model_fetcher.py
Fetches an model from the the HuggingFace library and runs an inference through it