Practical overview
When it fits
Use Openprompt when building or studying a prompt-learning pipeline for an NLP task and you want to compose a pretrained language model, input template, and verbalizer within one framework.
Who it is for
- NLP developers prototyping prompt-learning methods for pretrained language models.
- Researchers building prompt-based tuning or classification experiments.
- Teams that want a modular framework for defining task examples, templates, verbalizers, and model workflows.
Documented uses
- Prototype prompt-learning approaches for a downstream NLP task.
- Create a prompt-based tuning experiment using task examples and a pretrained language model.
- Train a prompt model or perform inference, including the README’s illustrated zero-shot classification workflow.
- Explore implemented prompting approaches and adapt them to a research idea.
Requirements & limits
The project is described as open source under the Apache-2.0 license. The README documents pip installation and source installation; it specifies Python 3.8+ and PyTorch 1.8.1+ for its tested setup.
- The project’s documented workflow requires choosing a pretrained language model suited to the task; the README notes that model attributes differ.
- Template and verbalizer design are central parts of the pipeline, so task labels and input format need to be defined.
- The README says some documentation is outdated after major changes; consult the tutorial scripts and documentation alongside it.
- The repository identifies Python as its primary language and gives Python 3.8+ and PyTorch 1.8.1+ as setup requirements.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Install Openprompt from its source repository
Set up the project from a cloned repository for local development.
Before you start
- Python 3.8 or later
- PyTorch 1.8.1 or later
- Git and a Python environment that can install project requirements
Steps
Clone https://github.com/thunlp/OpenPrompt.git.
Change into the OpenPrompt directory.
Install the listed requirements with pip install -r requirements.txt.
Install the package with python setup.py install. For editable development, the README also lists python setup.py develop.
Expected outcome
The README provides a source-based installation path and an editable-development command.
Guide limitations
- The README notes that parts of the documentation are outdated following major changes.
- This setup guidance does not establish that a particular model, task, or runtime environment will work.
Compare options for Model inference and serving
These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.
| Project | Documented purpose | Platform | Access and requirements |
|---|---|---|---|
| Openprompt | Prototype prompt-learning approaches for a downstream NLP task. | The project is described as open source under the Apache-2.0 license. The README documents pip installation and source installation; it specifies Python 3.8+ and PyTorch 1.8.1+ for its tested setup. | |
| Hyperpose | Customize pose-estimation architectures and datasets. | Docker, Linux, macOS, Windows | |
| Multi Task Nlp | Define multiple tasks and their data and model settings in a YAML file. | Linux, macOS, Windows | The project is an open-source library under the Apache-2.0 license, distributed through its public GitHub repository. |
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 15 October 2026
- Original website title
- thunlp/OpenPrompt · Official homepage title · retained in its source language