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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Zero and Few shot named entity & relationships recognition
| Date | Stars |
|---|---|
| 2026-07-24 | 400 |
| 2026-07-25 | 400 |
| 2026-07-28 | 400 |
| 2026-07-30 | 400 |
| 2026-08-15 | 401 |
| 2026-09-14 | 402 |
| 2026-09-17 | 402 |
| 2026-09-20 | 402 |
Today
— stars today
This week
+1 stars this week
This month
+1 stars this month
Momentum
0.0
growth rate 0.25%/day
<div align="center">
<img height="170x" src="https://ibm.github.io/zshot/img/graph.png" />
<h1>Zshot</h1>
<p>
<strong>Zero and Few shot named entity & relationships recognition</strong>
</p>
<p>
<a href="https://ibm.github.io/zshot/"><img alt="Tutorials" src="https://img.shields.io/badge/docs-tutorials-green" /></a>
<a href="https://pypi.org/project/zshot/"><img src="https://img.shields.io/pypi/v/zshot" /></a>
<a href="https://pypi.org/project/zshot/"><img src="https://img.shields.io/pypi/dm/zshot" /></a>
<a href="https://github.com/IBM/zshot/actions/workflows/python-tests.yml"> <img alt="Build" src="https://github.com/IBM/zshot/actions/workflows/python-tests.yml/badge.svg" /></a>
<a href="https://app.codecov.io/github/ibm/zshot"> <img alt="Build" src="https://codecov.io/github/ibm/zshot/branch/main/graph/badge.svg" /></a>
</p>
</div>
**Documentation**: <a href="https://ibm.github.io/zshot/" target="_blank">https://ibm.github.io/zshot</a>
**Source Code**: <a href="https://github.com/IBM/zshot" target="_blank">https://github.com/IBM/zshot</a>
**Paper**: <a href="https://aclanthology.org/2023.acl-demo.34/" target="_blank">https://aclanthology.org/2023.acl-demo.34/</a>
Zshot is a highly customisable framework for performing Zero and Few shot named entity recognition.
Can be used to perform:
- **Mentions extraction**: Identify globally relevant mentions or mentions relevant for a given domain
- **Wikification**: The task of linking textual mentions to entities in Wikipedia
- **Zero and Few Shot named entity recognition**: using language description perform NER to generalize to unseen domains
- **Zero and Few Shot named relationship recognition**
- **Visualization: Zero-shot NER and RE extraction**
## Requirements
* `Python 3.6+`
* <a href="https://spacy.io/" target="_blank"><code>spacy</code></a> - Zshot rely on <a href="https://spacy.io/" class="external-link" target="_blank">Spacy</a> for pipelining and visualization
* <a href="https://pytorch.org/get-started" target="_blank"><code>torch</code></a> - PyTorch is required to run pytorch models.
* <a href="https://huggingface.co/docs/transformers/index" target="_blank"><code>transformers</code></a> - Required for pre-trained language models.
* <a href="https://huggingface.co/docs/evaluate/index" target="_blank"><code>evaluate</code></a> - Required for evaluation.
* <a href="https://huggingface.co/docs/datasets/index" target="_blank"><code>datasets</code></a> - Required to evaluate over datasets (e.g.: OntoNotes).
### Optional Dependencies
* <a href="https://github.com/flairNLP/flair" target="_blank"><code>flair</code></a> - Required if you want to use Flair mentions extractor and for TARS linker and TARS Mentions Extractor.
* <a href="https://github.com/facebookresearch/BLINK" target="_blank"><code>blink</code></a> - Required if you want to use Blink for linking to Wikipedia pages.
* <a href="https://github.com/urchade/GLiNER" target="_blank"><code>gliner</code></a> - Required if you want to use GLiNER Linker or GLiNER Mentions Extractor.
* <a href="https://github.com/SapienzaNLP/relik" target="_blank"><code>relik</code></a> - Required if you want to use Relik Linker.
## Installation
<div class="termy">
```console
$ pip install zshot
---> 100%
```
</div>
## Examples
| Example | Notebook |
|:------------------------------:|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Installation and Visualization | [](https://colab.research.google.com/github/IBM/zshot/blob/examples/Zshot%20Example.ipynb) Excerpt of 17,096 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:3f0499034df522f7, topic:nlp, topic:natural-language-processing, topic:named-entity-recognition
matched fp:3f0499034df522f7, topic:deep-learning, topic:pytorch