Update README.md
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README.md
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@@ -97,8 +97,8 @@ query = "How many people live in London?"
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docs = ["Around 9 Million people live in London", "London is known for its financial district"]
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# Load model from HuggingFace Hub
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tokenizer = AutoTokenizer.from_pretrained("
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model = AutoModel.from_pretrained("
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#Encode query and docs
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query_emb = encode(query)
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@@ -154,8 +154,8 @@ query = "How many people live in London?"
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docs = ["Around 9 Million people live in London", "London is known for its financial district"]
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# Load model from HuggingFace Hub
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tokenizer = AutoTokenizer.from_pretrained("
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model = TFAutoModel.from_pretrained("
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#Encode query and docs
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query_emb = encode(query)
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docs = ["Around 9 Million people live in London", "London is known for its financial district"]
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# Load model from HuggingFace Hub
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tokenizer = AutoTokenizer.from_pretrained("SeyedAli/Multilingual-Text-Semantic-Search-Siamese-BERT-V1")
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model = AutoModel.from_pretrained("SeyedAli/Multilingual-Text-Semantic-Search-Siamese-BERT-V1")
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#Encode query and docs
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query_emb = encode(query)
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docs = ["Around 9 Million people live in London", "London is known for its financial district"]
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# Load model from HuggingFace Hub
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tokenizer = AutoTokenizer.from_pretrained("SeyedAli/Multilingual-Text-Semantic-Search-Siamese-BERT-V1")
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model = TFAutoModel.from_pretrained("SeyedAli/Multilingual-Text-Semantic-Search-Siamese-BERT-V1")
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#Encode query and docs
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query_emb = encode(query)
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