metadata
datasets:
- Bo1015/ssp_q3
base_model:
- genbio-ai/AIDO.Protein-16B
LoRA fine-tuned checkpoint for ssp_q3.
How to Use
Download model
from huggingface_hub import snapshot_download
from pathlib import Path
model_name = "genbio-ai/AIDO.Protein-16B-ssp_q3"
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
import torch
from modelgenerator.tasks import TokenClassification
ckpt_path = genbio_models_path.joinpath('model.ckpt')
model = TokenClassification.load_from_checkpoint(ckpt_path, strict_loading=False).eval()
collated_batch = model.transform({"sequences": ["ACGT", "AGCT"]})
logits = model(collated_batch)
print(logits)
print(torch.argmax(logits, dim=-1))