Views
No views yet
transformers
Mamba2Config format), so load it with mamba-ssm directly:1from mamba_ssm.models.mixer_seq_simple import MambaLMHeadModel
2from transformers import AutoTokenizer
3
4model = MambaLMHeadModel.from_pretrained("zmzfpc/biomamba-1.3b", device="cuda", dtype="bfloat16")
5tokenizer = AutoTokenizer.from_pretrained("zmzfpc/biomamba-1.3b")AutoModelForCausalLM.from_pretrained will not work on this config.cyrilzakka/pubmed-medline (revision 432681e19469e93e6c42878d5f41fec400974fb8)wikimedia/wikipedia, config 20231101.en (revision b04c8d1ceb2f5cd4588862100d08de323dccfbaa)allenai/c4, config en (revision 1588ec454efa1a09f29cd18ddd04fe05fc8653a2)1@article{yue2024biomamba,
2 title = {{BioMamba}: Domain-Adaptive Biomedical Language Models},
3 author = {Yue, Ling and Zhu, Mingzhi and Xing, Sixue and Pan, Shaowu and
4 Chenthamarakshan, Vijil and Wang, Yanbo and Cao, Yunning and
5 Das, Payel and Fu, Tianfan},
6 journal = {arXiv preprint arXiv:2408.02600},
7 year = {2024}
8}