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---
tags:
- flair
- hunflair
- token-classification
- sequence-tagger-model
language: en
widget:
- text: It contains a functional GCGGCGGCG Egr-1-binding site
---
## HunFlair2 model for TFBS
[HunFlair](https://github.com/flairNLP/flair/blob/master/resources/docs/HUNFLAIR2.md) (biomedical flair) for enhancer entity:
- pre-trained language model: michiyasunaga/BioLinkBERT-base
- fine-tuned on RegEl corpus for `Tfbs` entity type
Predicts 1 tag:
| **tag** | **meaning** |
| ------- | ---------------------------------------- |
| Tfbs | DNA region bound by transcription factor |
______________________________________________________________________
## Info
### Demo: How to use in Flair
Requires:
- **[Flair](https://github.com/flairNLP/flair/)>=0.14.0** (`pip install flair` or `pip install git+https://github.com/flairNLP/flair.git`)
```python
from flair.data import Sentence
from flair.nn import Classifier
from flair.tokenization import SciSpacyTokenizer
text = "We found that Egr-1 specifically binds to the PTEN 5' untranslated region, which contains a functional GCGGCGGCG Egr-1-binding site."
sentence = Sentence(text, use_tokenizer=SciSpacyTokenizer())
tagger = Classifier.load("regel-corpus/hunflair2-regel-tfbs")
tagger.predict(sentence)
print('The following NER tags are found:')
# iterate over entities and print
for entity in sentence.get_spans('ner'):
print(entity)
```
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