---
license: other
---
# AIDO.Protein-16B-v1

AIDO.Protein-16B-v1 continues the pre-training of [AIDO.Protein-16B](https://huggingface.co/genbio-ai/AIDO.Protein-16B) using an additional 100 billion amino acids from Uniref90.


## How to Use
### Build any downstream models from this backbone with ModelGenerator
For more information, visit: [Model Generator](https://github.com/genbio-ai/modelgenerator)
```bash
mgen fit --model SequenceClassification --model.backbone aido_protein_16b_v1 --data SequenceClassificationDataModule --data.path <hf_or_local_path_to_your_dataset>
mgen test --model SequenceClassification --model.backbone aido_protein_16b_v1 --data SequenceClassificationDataModule --data.path <hf_or_local_path_to_your_dataset>
```

### Or use directly in Python
#### Embedding
```python
from modelgenerator.tasks import Embed
model = Embed.from_config({"model.backbone": "aido_protein_16b_v1"}).eval()
transformed_batch = model.transform({"sequences": ["HELLQ", "WRLD"]})
embedding = model(transformed_batch)
print(embedding.shape)
print(embedding)
```
#### Sequence Level Classification
```python
import torch
from modelgenerator.tasks import SequenceClassification
model = SequenceClassification.from_config({"model.backbone": "aido_protein_16b_v1", "model.n_classes": 2}).eval()
transformed_batch = model.transform({"sequences": ["HELLQ", "WRLD"]})
logits = model(transformed_batch)
print(logits)
print(torch.argmax(logits, dim=-1))
```
#### Token Level Classification
```python
import torch
from modelgenerator.tasks import TokenClassification
model = TokenClassification.from_config({"model.backbone": "aido_protein_16b_v1", "model.n_classes": 3}).eval()
transformed_batch = model.transform({"sequences": ["HELLQ", "WRLD"]})
logits = model(transformed_batch)
print(logits)
print(torch.argmax(logits, dim=-1))
```
#### Regression
```python
from modelgenerator.tasks import SequenceRegression
model = SequenceRegression.from_config({"model.backbone": "aido_protein_16b_v1"}).eval()
transformed_batch = model.transform({"sequences": ["HELLQ", "WRLD"]})
logits = model(transformed_batch)
print(logits)
```

# Citation
Please cite AIDO.Protein using the following BibTex code:
```
@inproceedings{sun_mixture_2024,
	title = {Mixture of Experts Enable Efficient and Effective Protein Understanding and Design},
	url = {https://www.biorxiv.org/content/10.1101/2024.11.29.625425v1},
	doi = {10.1101/2024.11.29.625425},
	publisher = {bioRxiv},
	author = {Sun, Ning and Zou, Shuxian and Tao, Tianhua and Mahbub, Sazan and Li, Dian and Zhuang, Yonghao and Wang, Hongyi and Cheng, Xingyi and Song, Le and Xing, Eric P.},
	year = {2024},
    booktitle={NeurIPS 2024 Workshop on AI for New Drug Modalities},
}
```