参考：
https://github.com/facebookresearch/esm
https://huggingface.co/facebook/esm2_t33_650M_UR50D
https://esmatlas.com/resources?action=fold文章来源：https://www.toymoban.com/news/detail-608810.html
1、transformers版本使用
直接输入Fasta 氨基酸序列格式就行；第一次下载esm2_t33_650M_UR50D模型有点慢,有2个多G大文章来源地址https://www.toymoban.com/news/detail-608810.html
from transformers import BertTokenizer, AutoTokenizer,BertModel, AutoModel
tokenizer_ = AutoTokenizer.from_pretrained("facebook/esm2_t33_650M_UR50D")
model_ = AutoModel.from_pretrained("facebook/esm2_t33_650M_UR50D")
outputs_ = model_(**tokenizer_("MEILCEDNISLSSIPNSLMQLGDGPRLYHNDFNSRDANTSEASNWTIDAENRTNLSCEGYLPPTCLSILHLQEKNWSALLTTVVIILTIAGNILVIMAVSLEKKLQNATNYFLMSLAIADMLLGFLVMPVSMLTILYGYRWPLPSKLCAIWIYLDVLFSTASIMHLCAISLDRYVAIQNPIHHSRFNSRTKAFLKIIAVWTISVGISMPIPVFGLQDDSKVFKEGSCLLADDNFVLIGSFVAFFIPLTIMVITYFLTIKSLQKEATLCVSDLSTRAKLASFSFLPQSSLSSEKLFQRSIHREPGSYAGRRTMQSISNEQKACKVLGIVFFLFVVMWCPFFITNIMAVICKESCNENVIGALLNVFVWIGYLSSAVNPLVYTLFNKTYRSAFSRYIQCQ到了这里，关于ESM2蛋白预训练模型 蛋白质、氨基酸向量表示的文章就介绍完了。如果您还想了解更多内容，请在右上角搜索TOY模板网以前的文章或继续浏览下面的相关文章，希望大家以后多多支持TOY模板网！
