Hi folks,
I was working on a personal experimental project related to GPT-3, which I thought of making it open source now. It saves much time while working with LLMs.
If you are an industrial researcher or application developer, you probably have worked with GPT-3 apis.
A common challenge when utilizing LLMs such as #GPT-3 and BLOOM is their tendency to produce uncontrollable & unstructured outputs, making it difficult to use them for various NLP tasks and applications.
To address this, we developed Promptify, a library that allows for the use of LLMs to solve NLP problems, including Named Entity Recognition, Binary Classification, Multi-Label Classification, and Question-Answering and return a python object for easy parsing to construct additional applications on top of GPT-n based models.
Features 🚀
🧙♀️ NLP Tasks (NER, Binary Text Classification, Multi-Label Classification etc) in 2 lines of code with no training data required
🔨 Easily add one shot, two shot, or few shot examples to the prompt
✌ Output always provided as a Python object (e.g. list, dictionary) for easy parsing and filtering
💥 Custom examples and samples can be easily added to the prompt
💰 Optimized prompts to reduce OpenAI token costs
GITHUB: https://github.com/promptslab/Promptify
Examples: https://github.com/promptslab/Promptify/tree/main/examples
For quick demo -> Colab
Try out and share your feedback. Thanks :)
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discord.gg/m88xfYMbK6
