5-fold cross-validation LoRA fine-tuned checkpoints for protein abundance prediction (hsapiens).

How to Use

Download model

from huggingface_hub import snapshot_download
from pathlib import Path

model_name = "genbio-ai/AIDO.RNA-1.6B-CDS-protein-abundance-hsapiens"
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

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)
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