Update README.md

README.md

@@ -70,8 +70,8 @@ def mean_pooling(model_output, attention_mask):
 sentences = ['This is an example sentence', 'Each sentence is converted']
 
 # Load model from HuggingFace Hub
-tokenizer = AutoTokenizer.from_pretrained('MiniLM-L6-dmr')
-model = AutoModel.from_pretrained('MiniLM-L6-dmr')
+tokenizer = AutoTokenizer.from_pretrained('McGill-NLP/MiniLM-L6-dmr')
+model = AutoModel.from_pretrained('McGill-NLP/MiniLM-L6-dmr')
 
 # Tokenize sentences
 encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt')
@@ -93,7 +93,7 @@ print(sentence_embeddings)
 
 <!--- Describe how your model was evaluated -->
 
-For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name=MiniLM-L6-dmr)
+For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name=McGill-NLP/MiniLM-L6-dmr)
 
 
 ## Training