Caduceus-PS fish20 adapted

This checkpoint is Caduceus-PS adapted to the FishNALM 20-species fish-genome corpus for masked language modeling.

Domain-adaptive pretraining

Setting Value
Base model Caduceus-PS (~7.7M parameters)
Tokenization Single nucleotide
Hardware 4 × NVIDIA A100 80GB
Per-device batch size 64
Gradient accumulation steps 1
Effective global batch size 256
Peak learning rate 1 × 10⁻⁴
Corpus exposure 1 epoch

Usage

This repository contains custom model and tokenizer code. Load it with trust_remote_code=True.

from transformers import AutoModelForMaskedLM, AutoTokenizer

model_id = "<your-namespace>/Caduceus-PS-fish20-adapted"
tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForMaskedLM.from_pretrained(model_id, trust_remote_code=True)

The checkpoint is intended for DNA-sequence representation and masked-token prediction. Evaluate and adapt it for each downstream task before use.

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