kyegomez/GPT3

An implementation of the base GPT-3 Model architecture from the paper by OPENAI "Language Models are Few-Shot Learners"

34
/ 100
Emerging

This project offers a foundational implementation of the GPT-3 language model architecture, enabling you to build powerful language understanding and generation systems. It takes in raw text or numerical representations of text and produces contextually relevant text outputs. Researchers and engineers working with large language models would use this to experiment with few-shot learning capabilities for various NLP tasks.

No commits in the last 6 months.

Use this if you are an AI researcher or machine learning engineer looking to understand, replicate, or build upon the core GPT-3 architecture for advanced natural language processing tasks.

Not ideal if you are a practitioner looking for a ready-to-use, pre-trained GPT-3 model for immediate application without deep technical setup or customization.

Natural Language Processing Large Language Models Few-Shot Learning AI Research Text Generation
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 12 / 25

How are scores calculated?

Stars

20

Forks

3

Language

Python

License

MIT

Last pushed

Jun 29, 2024

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/kyegomez/GPT3"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.