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.

Developed by: zhangtaolab

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 promoter strength in tobacco leaves system.

Install the runtime library first:

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).