The plant DNA large language models (LLMs) contain a series of foundation models based on different model architectures, which are pre-trained on various plant reference genomes.
All the models have a comparable model size between 90 MB and 150 MB, BPE tokenizer is used for tokenization and 8000 tokens are included in the vocabulary.
The model is trained based on the State-Space Mamba-130m model with modified tokenizer specific for DNA sequence.
This model is fine-tuned for predicting open chromatin.
1pip install transformers
2pip install causal-conv1d<=1.2.0
3pip install mamba-ssm<2.0.0
Since
transformers library (version < 4.43.0) does not provide a MambaForSequenceClassification function, we wrote a script to train Mamba model for sequence classification.
An inference code can be found in our
GitHub.
Note that Plant DNAMamba model requires NVIDIA GPU to run.
We use a custom MambaForSequenceClassification script to fine-tune the model.
Detailed training procedure can be found in our manuscript.
Model was trained on a NVIDIA GTX4090 GPU (24 GB).