File size: 1,398 Bytes
ad89901 ad0caba ad89901 d3aef1a ad0caba d3aef1a ad89901 ad0caba |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 |
---
datasets:
- genbio-ai/transcript_isoform_expression_prediction
metrics:
- spearmanr
- r_squared
base_model:
- genbio-ai/AIDO.RNA-1.6B-CDS
- EleutherAI/enformer-official-rough
tags:
- biology
---
# Bi-modal model for RNA isoform expression prediction
## RNA isoform expression prediction
* Input: dna_seq, rna_seq
* Output: expression level in 30 tissues
## Model architecture
* Backbones:
* DNA: Enformer (fully finetuning)
* RNA: AIDO.RNA-1.6B-CDS (lora finetuning)
* Fusion method: concat fusion
## Usage
**Download model**
```python
from huggingface_hub import snapshot_download
from pathlib import Path
model_name = "genbio-ai/AIDO.MM-Enformer-RNA-1.6B-CDS-ConcatFusion-rna-isoform-expression-ckpt"
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)
```
**Evaluation script**
Once you download the model, you can use the model in [ModelGenertor](https://github.com/genbio-ai/ModelGenerator) using the following script:
```bash
CONFIG_FILE=... # put the config file path here
CKPT_PATH=... # put the model checkpoint path here
mgen test --config $CONFIG_FILE \
--data.batch_size 16 \
--trainer.logger null \
--model.strict_loading False \
--model.reset_optimizer_states True \
--ckpt_path $CKPT_PATH
``` |