README.md

---
datasets:
- genbio-ai/rna-downstream-tasks
base_model:
- genbio-ai/AIDO.RNA-1.6B
---
10-fold cross-validation fully fine-tuned checkpoints for mRNA expression level prediction (pc3).

## How to Use
### Download model
```python
from huggingface_hub import snapshot_download
from pathlib import Path

model_name = "genbio-ai/AIDO.RNA-1.6B-mrna-expression-level-pc3"
genbio_models_path = Path.home().joinpath('genbio_models', model_name)
genbio_models_path.mkdir(parents=True, exist_ok=True)
snapshot_download(repo_id=model_name, local_dir=genbio_models_path)
```
### Load model for inference
```python
from modelgenerator.tasks import SequenceRegression

ckpt_path = genbio_models_path.joinpath('fold0', 'model.ckpt')
model = SequenceRegression.load_from_checkpoint(ckpt_path, strict_loading=False).eval()

collated_batch = model.transform({"sequences": ["ACGT", "AGCT"]})
logits = model(collated_batch)
print(logits)