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README.md
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- feature-extraction
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- sentence-transformers
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---
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#
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Mod of https://huggingface.co/intfloat/multilingual-e5-large.
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Shrink tokenizer to 32K (ru+en) with David's Dale [manual](https://towardsdatascience.com/how-to-adapt-a-multilingual-t5-model-for-a-single-language-b9f94f3d9c90) and invaluable assistance!
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Below is an example for usage with sentence_transformers.
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```python
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from sentence_transformers import SentenceTransformer
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model = SentenceTransformer('
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input_texts = ["passage: This is an example sentence", "passage: Каждый охотник желает знать.","query: Где сидит фазан?"]
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embeddings = model.encode(input_texts, normalize_embeddings=True)
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```
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- feature-extraction
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- sentence-transformers
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---
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# e5-large-ru
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Mod of https://huggingface.co/intfloat/multilingual-e5-large.
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Shrink tokenizer to 32K (ru+en) with David's Dale [manual](https://towardsdatascience.com/how-to-adapt-a-multilingual-t5-model-for-a-single-language-b9f94f3d9c90) and invaluable assistance!
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Below is an example for usage with sentence_transformers.
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```python
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from sentence_transformers import SentenceTransformer
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model = SentenceTransformer('Nehc/e5-large-ru')
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input_texts = ["passage: This is an example sentence", "passage: Каждый охотник желает знать.","query: Где сидит фазан?"]
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embeddings = model.encode(input_texts, normalize_embeddings=True)
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```
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