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tags: |
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- DNA |
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license: mit |
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--- |
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## MiniDNA mini model |
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This is a distilled version of [DNABERT](https://github.com/jerryji1993/DNABERT) by using MiniLM technique. It has a BERT architecture with 3 layers and 384 hidden units, pre-trained on 6-mer DNA sequences. For more details on the pre-training scheme and methods, please check the original thesis report _[link to be added]_. |
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## How to Use |
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The model can be used to fine-tune on a downstream genomic task, e.g. promoter identification. |
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```python |
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import torch |
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from transformers import BertForSequenceClassification |
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model = BertForSequenceClassification.from_pretrained('Peltarion/dnabert-minilm-mini') |
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``` |
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More details on how to fine-tune the model, dataset and additional source codes are available on [github.com/joanaapa/Distillation-DNABERT-Promoter](https://github.com/joanaapa/Distillation-DNABERT-Promoter). |
