NbAiLab
/

nb-sbert-base

Sentence Similarity

sentence-transformers

feature-extraction

text-embeddings-inference

Model card Files Files and versions

pere commited on Nov 18, 2022

Commit

3f15bd5

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1 Parent(s): 5b514a7

Update README.md

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README.md +2 -2

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@@ -54,8 +54,8 @@ 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('{MODEL_NAME}')
-model = AutoModel.from_pretrained('{MODEL_NAME}')
 # Tokenize sentences
 encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt')

 sentences = ['This is an example sentence', 'Each sentence is converted']
 # Load model from HuggingFace Hub
+tokenizer = AutoTokenizer.from_pretrained('NbAiLab/nb-sbert')
+model = AutoModel.from_pretrained('NbAiLab/nb-sbert')
 # Tokenize sentences
 encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt')