Solve NLP Problems with LLM's & Easily generate different NLP Task prompts for popular generative models like GPT, PaLM, and more with Promptify
This repository is tested on Python 3.7+, openai 0.25+.
You should install Promptify using Pip command
pip install promptify
To immediately use a LLM model for your NLP task, we provide the Prompter
API.
- Perform NLP tasks (such as NER and classification) in just 2 lines of code, with no training data required
- Easily add one shot, two shot, or few shot examples to the prompt
- Handling out-of-bounds prediction from LLMS (GPT, t5, etc.)
- Output always provided as a Python object (e.g. list, dictionary) for easy parsing and filtering. This is a major advantage over LLMs generated output, whose unstructured and raw output makes it difficult to use in business or other applications.
- Custom examples and samples can be easily added to the prompt
- Optimized prompts to reduce OpenAI token costs (coming soon)
Task Name | Colab Notebook | Status |
---|---|---|
Named Entity Recognition | NER Examples with GPT-3 | ✅ |
Multi-Label Text Classification | Classification Examples with GPT-3 | ✅ |
Multi-Class Text Classification | Classification Examples with GPT-3 | ✅ |
Binary Text Classification | Classification Examples with GPT-3 | ✅ |
Question-Answering | QA Task Examples with GPT-3 | ✅ |
Question-Answer Generation | QA Task Examples with GPT-3 | ✅ |
Summarization | Summarization Task Examples with GPT-3 | ✅ |
Explanation | Explanation Task Examples with GPT-3 | ✅ |
Tabular Data | ||
Image Data | ||
More Prompts |