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Update README.md

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@@ -31,7 +31,10 @@ Then you can use the model like this:
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  from sentence_transformers import SentenceTransformer
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  from sentence_transformers.util import cos_sim
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- sentences = ["ื”ื ื”ื™ื• ืฉืžื—ื™ื ืœืจืื•ืช ืืช ื”ืื™ืจื•ืข ืฉื”ืชืงื™ื™ื.", "ืœืจืื•ืช ืืช ื”ืื™ืจื•ืข ืฉื”ืชืงื™ื™ื ื”ื™ื” ืžืื•ื“ ืžืฉืžื— ืœื”ื."]
 
 
 
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  model = SentenceTransformer('imvladikon/sentence-transformers-alephbert')
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  embeddings = model.encode(sentences)
@@ -60,7 +63,10 @@ def mean_pooling(model_output, attention_mask):
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  # Sentences we want sentence embeddings for
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- sentences = ["ื”ื ื”ื™ื• ืฉืžื—ื™ื ืœืจืื•ืช ืืช ื”ืื™ืจื•ืข ืฉื”ืชืงื™ื™ื.", "ืœืจืื•ืช ืืช ื”ืื™ืจื•ืข ืฉื”ืชืงื™ื™ื ื”ื™ื” ืžืื•ื“ ืžืฉืžื— ืœื”ื."]
 
 
 
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  # Load model from HuggingFace Hub
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  tokenizer = AutoTokenizer.from_pretrained('imvladikon/sentence-transformers-alephbert')
 
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  from sentence_transformers import SentenceTransformer
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  from sentence_transformers.util import cos_sim
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+ sentences = [
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+ "ื”ื ื”ื™ื• ืฉืžื—ื™ื ืœืจืื•ืช ืืช ื”ืื™ืจื•ืข ืฉื”ืชืงื™ื™ื.",
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+ "ืœืจืื•ืช ืืช ื”ืื™ืจื•ืข ืฉื”ืชืงื™ื™ื ื”ื™ื” ืžืื•ื“ ืžืฉืžื— ืœื”ื."
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+ ]
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  model = SentenceTransformer('imvladikon/sentence-transformers-alephbert')
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  embeddings = model.encode(sentences)
 
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  # Sentences we want sentence embeddings for
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+ sentences = [
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+ "ื”ื ื”ื™ื• ืฉืžื—ื™ื ืœืจืื•ืช ืืช ื”ืื™ืจื•ืข ืฉื”ืชืงื™ื™ื.",
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+ "ืœืจืื•ืช ืืช ื”ืื™ืจื•ืข ืฉื”ืชืงื™ื™ื ื”ื™ื” ืžืื•ื“ ืžืฉืžื— ืœื”ื."
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+ ]
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  # Load model from HuggingFace Hub
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  tokenizer = AutoTokenizer.from_pretrained('imvladikon/sentence-transformers-alephbert')