Update README.md

README.md

@@ -30,8 +30,8 @@ We evaluated the ProteinPGLM-MLM (PGLM) and ProteinPGLM-INT4(100B) models on two
 from transformers import AutoModelForMaskedLM, AutoModelForSequenceClassification, AutoModelForTokenClassification, AutoTokenizer, AutoConfig
 import torch
 
-tokenizer  = AutoTokenizer.from_pretrained("Bo1015/proteinglm-1b-mlm", trust_remote_code=True, use_fast=True)
-model = AutoModelForMaskedLM.from_pretrained("Bo1015/proteinglm-1b-mlm",  trust_remote_code=True, torch_dtype=torch.bfloat16)
+tokenizer  = AutoTokenizer.from_pretrained("proteinglm/proteinglm-1b-mlm", trust_remote_code=True, use_fast=True)
+model = AutoModelForMaskedLM.from_pretrained("proteinglm/proteinglm-1b-mlm",  trust_remote_code=True, torch_dtype=torch.bfloat16)
 if torch.cuda.is_available():
     model = model.cuda()
 model.eval()
@@ -44,10 +44,10 @@ with torch.inference_mode():
 
 
 # model for the sequence-level tasks
-model = AutoModelForSequenceClassification.from_pretrained("Bo1015/proteinglm-10b-mlm",  trust_remote_code=True, torch_dtype=torch.bfloat16)
+model = AutoModelForSequenceClassification.from_pretrained("proteinglm/proteinglm-10b-mlm",  trust_remote_code=True, torch_dtype=torch.bfloat16)
 
 # model for the token-level tasks
-model = AutoModelForTokenClassification.from_pretrained("Bo1015/proteinglm-10b-mlm",  trust_remote_code=True, torch_dtype=torch.bfloat16)
+model = AutoModelForTokenClassification.from_pretrained("proteinglm/proteinglm-10b-mlm",  trust_remote_code=True, torch_dtype=torch.bfloat16)
 
 ```