Update links

README.md

@@ -1,7 +1,7 @@
 ---
 license: mit
 datasets:
-  - drug-discovery/UR100P
+  - chandar-lab/UR100P
 language:
   - en
 tags:
@@ -73,14 +73,14 @@ from transformers import AutoTokenizer
 from datasets import load_dataset
 
 # Load AMPLIFY and tokenizer
-model = AutoModel.from_pretrained("drug-discovery/AMPLIFY_350M", trust_remote_code=True)
-tokenizer = AutoTokenizer.from_pretrained("drug-discovery/AMPLIFY_350M", trust_remote_code=True)
+model = AutoModel.from_pretrained("chandar-lab/AMPLIFY_350M", trust_remote_code=True)
+tokenizer = AutoTokenizer.from_pretrained("chandar-lab/AMPLIFY_350M", trust_remote_code=True)
 
 # Move the model to GPU (required due to Flash Attention)
 model = model.to("cuda")
 
 # Load the UniProt validation set
-dataset = load_dataset("drug-discovery/UR100P", data_dir="UniProt", split="test")
+dataset = load_dataset("chandar-lab/UR100P", data_dir="UniProt", split="test")
 
 for sample in dataset:
     # Protein