Update README.md

README.md

@@ -9,6 +9,8 @@ tags:
 
 **This is repository for MutBERT (pretrained with mutation data in human genome)**.
 
+**You can find all MutBERT variants at [here](https://huggingface.co/JadenLong).**
+
 ## Introduction
 
 This is the official pre-trained model introduced in MutBERT: Probabilistic Genome Representation Improves Genomics Foundation Models.
@@ -30,6 +32,7 @@ MutBERT is a transformer-based genome foundation model trained only on Human gen
 from transformers import AutoTokenizer, AutoModel
 
 model_name = "JadenLong/MutBERT"
+# Optional: JadenLong/MutBERT-Huamn-Ref, JadenLong/MutBERT-Multi
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = AutoModel.from_pretrained(model_name, trust_remote_code=True)
 ```
@@ -45,6 +48,7 @@ import torch.nn.functional as F
 from transformers import AutoTokenizer, AutoModel
 
 model_name = "JadenLong/MutBERT"
+# Optional: JadenLong/MutBERT-Huamn-Ref, JadenLong/MutBERT-Multi
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = AutoModel.from_pretrained(model_name, trust_remote_code=True)
 
@@ -70,6 +74,7 @@ print(embedding_max.shape) # expect to be 768
 from transformers import AutoModelForSequenceClassification
 
 model_name = "JadenLong/MutBERT"
+# Optional: JadenLong/MutBERT-Huamn-Ref, JadenLong/MutBERT-Multi
 model = AutoModelForSequenceClassification.from_pretrained(model_name, trust_remote_code=True, num_labels=2)
 ```
 
@@ -81,6 +86,7 @@ If you want to scale your model context by 2x:
 
 ```python
 model_name = "JadenLong/MutBERT"
+# Optional: JadenLong/MutBERT-Huamn-Ref, JadenLong/MutBERT-Multi
 model = AutoModel.from_pretrained(model_name,
                                   trust_remote_code=True,
                                   rope_scaling={'type': 'dynamic','factor': 2.0}