---
language:
- dna
tags:
- biology
- genomics
- transposable-elements
- dnabert
- bilstm
- sequence-classification
license: mit
---

# TE-GER — Binary Detection

Part of the **TE-GER** (Transposable Elements Genomic Entity Recognition) toolkit.

TE-GER binary model: detects presence/absence of Transposable Elements (TE vs Background) in genomic sequences. Architecture: DNABERT-2 + BiLSTM hybrid. Labels: Background, TE.

## Model Architecture

- **Base:** [DNABERT-2](https://huggingface.co/zhihan1996/DNABERT-2-117M) (DNA language model)
- **Head:** Bidirectional LSTM + Linear Classifier
- **Input:** 512 bp sliding windows over raw FASTA sequences
- **Task:** Sequence classification (token-level TE annotation)

## Usage

Use this model via the [TE-GER CLI](https://github.com/johanpina/te-ger):

```bash
python Te_annotator.py genome.fasta output.gff3 --level binary
```

## Labels

- `0`: Background
- `1`: TE

## Citation

Developed by Johan S. Piña — 2025