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Prompt-learning is the latest paradigm to adapt pre-trained language models (PLMs) to downstream NLP tasks, which modifies the input text with a textual template and directly uses PLMs to conduct pre-trained tasks. OpenPrompt is a library built upon PyTorch and provides a standard, flexible and extensible framework to deploy the prompt-learning pipeline. OpenPrompt supports loading PLMs directly from huggingface transformers. In the future, we will also support PLMs implemented by other libraries. The template is one of the most important modules in prompt learning, which wraps the original input with textual or soft-encoding sequence. Use the implementations of current prompt-learning approaches.* We have implemented various of prompting methods, including templating, verbalizing and optimization strategies under a unified standard. You can easily call and understand these methods.
Features
- Design your own prompt-learning work
- With the extensibility of OpenPrompt, you can quickly practice your prompt-learning ideas
- Our repo is tested on Python 3.8+ and PyTorch 1.8.1+
- You can easily develop a prompt-learning pipeline
- Define a Pre-trained Language Models (PLMs) as backbone.
- Define a Verbalizer
Project Samples
