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FishCaduceus-28L-512-FishGUE
FishCaduceus/FishCaduceus-28L-512-FishGUE
FishCaduceus-28L-512-FishGUE is a machine learning model from FishCaduceus. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
FishCaduceus-28L-512-FishGUE is a collection of 17 task-specific models obtained by fine-tuning the pretrained FishCaduceus-28L-512 DNA language model on downstream fish genomic function prediction tasks from FishGUE.
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Updated Jul 11, 2026
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At a glance
- Library
- transformers
- Access
- Public
- Created
- Jul 11, 2026
- Updated
- Jul 11, 2026
- SHA
- e66a6746
Model card
From the Hugging Face model README
FishCaduceus-28L-512-FishGUE
FishCaduceus-28L-512-FishGUE is a collection of 17 task-specific models obtained by fine-tuning the pretrained FishCaduceus-28L-512 DNA language model on downstream fish genomic function prediction tasks from Fish_GUE.
Model description
This repository contains one FishCaduceus backbone family and one fine-tuned sequence-classification model for each included task. The original task directory names are retained so that the repository can be used with subfolder-based loading.
Base model
The base model is FishCaduceus/FishCaduceus-28L-512.
Included downstream tasks
| Task directory | Task description |
|---|---|
CTCF_TF | CTCF transcription factor binding site prediction |
H3k27ac | H3K27ac histone modification prediction |
H3K27me3 | H3K27me3 histone modification prediction |
H3K4me1 | H3K4me1 histone modification prediction |
H3K4me3 | H3K4me3 histone modification prediction |
H3K9me3 | H3K9me3 histone modification prediction |
Pou5f1_TF | Pou5f1 transcription factor binding site prediction |
Sox2_TF | Sox2 transcription factor binding site prediction |
prom_1k_all | Promoter prediction using 1-kb sequences |
prom_1k_notata | Promoter prediction using 1-kb sequences for the non-TATA promoter subset |
prom_1k_tata | Promoter prediction using 1-kb sequences for the TATA promoter subset |
prom_300_all | Promoter prediction using 300-bp sequences |
prom_300_notata | Promoter prediction using 300-bp sequences for the non-TATA promoter subset |
prom_300_tata | Promoter prediction using 300-bp sequences for the TATA promoter subset |
splice_acceptor | Splice acceptor site prediction |
splice_donor | Splice donor site prediction |
splice_all | Splice site classification |
Repository structure
The repository contains 17 task directories. Each task retains its original name and contains a configuration, model weight file, and tokenizer files where present.
Training data
These models were fine-tuned on the corresponding downstream genomic function prediction tasks from Fish_GUE. No task sample counts are asserted here.
Intended uses
The models are intended for research on fish genomic sequence representation and task-specific genomic function prediction.
Limitations
The task models reflect the training data and task definitions used by Fish_GUE. Transfer to other species, assemblies, sequence lengths, or label definitions should be validated independently.
How to use
The audited task configurations declare CaduceusForSequenceClassification, model_type: caduceus, binary or three-way label mappings through id2label/label2id, and an auto_map for Caduceus classes. Loading with Transformers is expected to require trust_remote_code=True and an environment that provides the referenced Caduceus implementation. The task directories do not contain custom Python implementation files, so standalone execution from this repository alone is not guaranteed.
Files in this repository
Intermediate checkpoints, test metrics, test predictions, and training argument files were deliberately excluded. Model weights, configurations, and tokenizer files needed by the original task exports were retained.
Citation
The FishCaduceus manuscript is in preparation. Citation information will be added after publication.
Acknowledgements
FishCaduceus was developed for research on fish genomes at the Institute of Hydrobiology, Chinese Academy of Sciences.
Contact
Xiao-Qin Xia
Institute of Hydrobiology, Chinese Academy of Sciences
Email: [email protected]
- Library
- transformers
- Languages
- en
- Created
- Jul 11, 2026
- Updated
- Jul 11, 2026