---
base_model:
- genbio-ai/AIDO.RNA-1.6B
---
# AIDO.RNA-1.6B-CDS

AIDO.RNA-1.6B-CDS is a domain adaptation model on the coding sequences. It was pre-trained on 9 million coding sequences released by Carlos et al. (2024) [1] based on our [AIDO.RNA-1.6B](https://huggingface.co/genbio-ai/AIDO.RNA-1.6B) model.

## How to Use
### Build any downstream models from this backbone
#### Embedding
```python
from genbio_finetune.tasks import Embed
model = Embed.from_config({"model.backbone": "aido_rna_1b600m_cds"}).eval()
collated_batch = model.collate({"sequences": ["ACGT", "AGCT"]})
embedding = model(collated_batch)
print(embedding.shape)
print(embedding)
```

#### Regression
```python
from genbio_finetune.tasks import SequenceRegression
model = SequenceRegression.from_config({"model.backbone": "aido_rna_1b600m_cds"}).eval()
collated_batch = model.collate({"sequences": ["ACGT", "AGCT"]})
logits = model(collated_batch)
print(logits)
```

#### Sequence Level Classification
```python
import torch
from genbio_finetune.tasks import SequenceClassification
model = SequenceClassification.from_config({"model.backbone": "aido_rna_1b600m_cds", "model.n_classes": 2}).eval()
collated_batch = model.collate({"sequences": ["ACGT", "AGCT"]})
logits = model(collated_batch)
print(logits)
print(torch.argmax(logits, dim=-1))
```

#### Token Level Classification
```python
import torch
from genbio_finetune.tasks import TokenClassification
model = TokenClassification.from_config({"model.backbone": "aido_rna_1b600m_cds", "model.n_classes": 3}).eval()
collated_batch = model.collate({"sequences": ["ACGT", "AGCT"]})
logits = model(collated_batch)
print(logits)
print(torch.argmax(logits, dim=-1))
```

#### Or use our one-liner CLI to finetune or evaluate any of the above!
```
mgen fit --model SequenceClassification --model.backbone aido_rna_1b600m_cds --data SequenceClassification --data.path <hf_or_local_path_to_your_dataset>
mgen test --model SequenceClassification --model.backbone aido_rna_1b600m_cds --data SequenceClassification --data.path <hf_or_local_path_to_your_dataset>
```
For more information, visit: [ModelGenerator](https://github.com/genbio-ai/modelgenerator)


## Reference
1. Carlos Outeiral and Charlotte M Deane. Codon language embeddings provide strong signals for use in protein engineering. Nature Machine Intelligence, 6(2):170–179, 2024.