
# Model card

## Model description
This model has been trained on *varKodes*. These are images encoding the genomic landscape of a species. For more information, visit the github of the [varKoder project](https://github.com/brunoasm/varKoder)

The model architecture follows timm/vit_large_patch32_224.orig_in21k but initialized with random weights with `vision_learner()` function in the fastai library.

## Intended uses & limitations
Since this is trained on highly specialized technical images, it is only intended for the purposes of genetic sequence identification.

## Training and evaluation data
The current iteration of the model has been trained to recognize 861 eukaryotic families as described in this preprint: 

de Medeiros BAS et al. 2024. A universal DNA barcode for the Tree of Life. ecoevoRxiv https://doi.org/10.32942/X24891

Outputs are multi-label predictions for each of the included families, with the following format `family:[NCBI Taxonomic ID]`. Check [NCBI Taxonomy](https://www.ncbi.nlm.nih.gov/taxonomy) to translate taxonomic IDs into taxon names.

{"language": ["en"], "license": "apache-2.0", "library_name": "fastai", "tags": ["fastai", "timm"]}
fastai pytorch timm en license:apache-2.0 region:us