AntigenLM: Structure-Aware DNA Language Modeling for Influenza
Paper • 2602.09067 • Published
How to use Moonn1205/AntigenLM-prediction-sequence with Transformers:
# Load model directly
from transformers import AutoTokenizer, GPTForFluMultiTask
tokenizer = AutoTokenizer.from_pretrained("Moonn1205/AntigenLM-prediction-sequence")
model = GPTForFluMultiTask.from_pretrained("Moonn1205/AntigenLM-prediction-sequence", device_map="auto")Generative head of AntigenLM that autoregressively forecasts the next time-window influenza HA/NA nucleotide block from three historical blocks.
Paper: AntigenLM: Structure-Aware DNA Language Modeling for Influenza (arXiv:2602.09067). Code: https://github.com/Moonn1205/AntigenLM
pip install huggingface_hub transformers==4.29.2 torch==1.13.1
from huggingface_hub import snapshot_download
snapshot_download(
repo_id="Moonn1205/AntigenLM-prediction-sequence",
local_dir="prediction_sequence",
local_dir_use_symlinks=False,
)
Then follow the instructions in the code repository to run inference.
pytorch_model.bin - model weightsconfig.json - GPT-2 backbone config + (classifier only) label2id / id2labelvocab.json, tokenizer_config.json, special_tokens_map.json, added_tokens.json - tokenizer