Use GPT or other prompt based models to get structured output
Project description
Promptify
Solve NLP Problems with LLM's & Easily generate different NLP Task prompts for popular generative models like GPT, PaLM, and more with Promptify
Features 🎮
- 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)
Available Prompts for different NLP Task :
| 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 |
Project details
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