---
license: mit
language:
- en
tags:
- biology
- genomics
- viral-classification
- transformer
- distilbert
---

# Viro-BERT

Whole-genome Transformer framework for viral pathogen classification across 14 viral classes using Chunk-and-Vote Late Fusion Consensus.

---

### Requirements

```bash
pip install torch transformers biopython

```

Tested on Python 3.8+ and PyTorch 1.13+ (supports CPU and CUDA).

---

### Files in Repository

* `sota_chunk_model.pth` — Trained PyTorch model weights (DistilBERT backbone, 6 layers, 12 heads, hidden dim 768).
* `config.json` — 130-token 3-mer vocabulary, hyperparameters, and 14 target class mappings.
* `predict.py` — Standalone inference script for FASTA sequence classification.

---

### Command-Line Usage (Python)

Classify viral sequences from a FASTA file:

```bash
python predict.py --fasta sample.fasta

```

Optional arguments:

```bash
python predict.py --fasta sample.fasta --weights sota_chunk_model.pth --config config.json --top_k 3 --cpu

```

---

### Execution via R

Run directly from an R environment via system command:

```R
system("python predict.py --fasta sample.fasta")

```

Or programmatically via the `reticulate` interface:

```R
library(reticulate)
py_run_file("predict.py")

```

---

### Target Viral Classes (14)

* Dengue Virus (`Dengue`)
* Enterovirus A (`EnteroA`)
* Enterovirus B (`EnteroB`)
* Hepatitis B Virus (`HBV`)
* Hepatitis C Virus (`HCV`)
* Human Papillomavirus (`HPV`)
* Human Alphaherpesvirus 1 (`HSV-1`)
* Influenza A Virus (`IAV`)
* Influenza B Virus (`IBV`)
* Influenza C Virus (`ICV`)
* Monkeypox Virus (`MPV`)
* Severe Fever with Thrombocytopenia Syndrome Virus (`SFTS`)
* West Nile Virus (`WNV`)
* Zika Virus (`Zika`)

---

### License

Open access under the MIT License.

```

```