imvladikon
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Update README.md
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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 = [
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model = SentenceTransformer('imvladikon/sentence-transformers-alephbert')
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embeddings = model.encode(sentences)
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@@ -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 = [
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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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"ืื ืืื ืฉืืืื ืืจืืืช ืืช ืืืืจืืข ืฉืืชืงืืื.",
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"ืืจืืืช ืืช ืืืืจืืข ืฉืืชืงืืื ืืื ืืืื ืืฉืื ืืื."
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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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"ืื ืืื ืฉืืืื ืืจืืืช ืืช ืืืืจืืข ืฉืืชืงืืื.",
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"ืืจืืืช ืืช ืืืืจืืข ืฉืืชืงืืื ืืื ืืืื ืืฉืื ืืื."
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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')
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