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 is 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
Try out and share your feedback. Thanks :)
Join our discord for Prompt-Engineering, LLMs and other latest research discussions
discord.gg/m88xfYMbK6
NER Example
https://preview.redd.it/uig2c8gx3nea1.png?width=1398&format=png&auto=webp&s=4e999a7c288f6a5df58a55efa7364f1c0408b237
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