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---
tags:
- flair
- hunflair
- token-classification
- sequence-tagger-model
language: en
widget:
- text: "Isolate an enhancer element located between -89 and -50 bp in PAI-1"
---
## HunFlair model for ENHANCER
[HunFlair](https://github.com/flairNLP/flair/blob/master/resources/docs/HUNFLAIR.md) (biomedical flair) for enhancer entity.
Predicts 1 tag:
| **tag** | **meaning** |
|---------------------------------|-----------|
| Enhancer | DNA enhancer region |
---
### Cite
Please cite the following paper when using this model.
```
@article{garda2022regel,
title={RegEl corpus: identifying DNA regulatory elements in the scientific literature},
author={Garda, Samuele and Lenihan-Geels, Freyda and Proft, Sebastian and Hochmuth, Stefanie and Sch{\"u}lke, Markus and Seelow, Dominik and Leser, Ulf},
journal={Database},
volume={2022},
year={2022},
publisher={Oxford Academic}
}
```
---
### Demo: How to use in Flair
Requires:
- **[Flair](https://github.com/flairNLP/flair/)** (`pip install flair`)
```python
from flair.data import Sentence
from flair.models import SequenceTagger
# for biomedical-specific tokenization:
# from flair.tokenization import SciSpacyTokenizer
# load tagger
tagger = SequenceTagger.load("regel-corpus/hunflair-promoter")
text = "An upstream activator of the mitogen-activated protein (MAP) kinase pathways was used to isolate an enhancer element located between -89 and -50 bp in PAI-1 promoter that was activated by MEKK-1."
# make example sentence
sentence = Sentence(text)
# for biomedical-specific tokenization:
# sentence = Sentence(text, use_tokenizer=SciSpacyTokenizer())
# predict NER tags
tagger.predict(sentence)
# print sentence
print(sentence)
# print predicted NER spans
print('The following NER tags are found:')
# iterate over entities and print
for entity in sentence.get_spans('ner'):
print(entity)
```
This yields the following output:
```
Span [18,19,20,21,22,23,24,25,26,27,28,29,30]: "enhancer element located between - 89 and - 50 bp in PAI-1 promoter" [− Labels: Enhancer (0.992)]
```
So, the entity "*enhancer element located between - 89 and - 50 bp in PAI-1*" (labeled as a **enhancer**) is found in the sentence.
Alternatively download all models locally and use the `MultiTagger` class.
```python
from flair.models import MultiTagger
tagger = [
'./models/hunflair-promoter/pytorch_model.bin',
'./models/hunflair-enhancer/pytorch_model.bin',
'./models/hunflair-tfbs/pytorch_model.bin',
]
tagger = MultiTagger.load(['./models/hunflair-'])
tagger.predict(sentence)
```
---
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