https://github.com/dohlee/proteinbert-pytorch
Implementation of ProteinBERT, a deep language model designed for proteins.
https://github.com/dohlee/proteinbert-pytorch
bert bert-model protein protein-language-model proteinbert transformer transformers transformers-bert
Last synced: 4 months ago
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Implementation of ProteinBERT, a deep language model designed for proteins.
- Host: GitHub
- URL: https://github.com/dohlee/proteinbert-pytorch
- Owner: dohlee
- Created: 2023-03-08T08:42:21.000Z (over 3 years ago)
- Default Branch: master
- Last Pushed: 2023-04-28T14:44:46.000Z (about 3 years ago)
- Last Synced: 2025-09-23T04:41:46.990Z (9 months ago)
- Topics: bert, bert-model, protein, protein-language-model, proteinbert, transformer, transformers, transformers-bert
- Language: Python
- Homepage:
- Size: 87.9 KB
- Stars: 3
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# proteinbert-pytorch
Implementation of ProteinBERT, a deep language model specifically designed for proteins.
The official implementation of ProteinBERT is available at [here](https://github.com/nadavbra/protein_bert).
## Installation
```bash
$ pip install proteinbert-pytorch-reproduction
```
## Usage
```python
from proteinbert_pytorch import ProteinBERT
vocab_size = 26
ann_size = 8943
seq_len = 512
bsz = 1
x_seq = torch.randint(0, vocab_size, (bsz, seq_len))
x_ann = torch.rand(bsz, ann_size)
model = ProteinBERT(vocab_size, ann_size)
x_seq_pred, x_ann_pred = model(x_seq, x_ann)
```
## Citations
```bibtex
@article{brandes2022proteinbert,
title={ProteinBERT: a universal deep-learning model of protein sequence and function},
author={Brandes, Nadav and Ofer, Dan and Peleg, Yam and Rappoport, Nadav and Linial, Michal},
journal={Bioinformatics},
volume={38},
number={8},
pages={2102--2110},
year={2022},
publisher={Oxford University Press}
}
```