Nehc
/

e5-large-ru

Feature Extraction

sentence-transformers

Sentence Transformers

sentence-similarity

Inference Endpoints

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Nehc commited on Mar 2

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@@ -11,7 +11,7 @@ tags:
 - feature-extraction
 - sentence-transformers
 ---
-# E5-large-ru
 Mod of https://huggingface.co/intfloat/multilingual-e5-large.
 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!
@@ -22,7 +22,7 @@ Thank you, David! 🥰
 Below is an example for usage with sentence_transformers.
 ```python
 from sentence_transformers import SentenceTransformer
-model = SentenceTransformer('intfloat/multilingual-e5-large')
 input_texts = ["passage: This is an example sentence", "passage: Каждый охотник желает знать.","query: Где сидит фазан?"]
 embeddings = model.encode(input_texts, normalize_embeddings=True)
 ```

 - feature-extraction
 - sentence-transformers
 ---
+# e5-large-ru
 Mod of https://huggingface.co/intfloat/multilingual-e5-large.
 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!
 Below is an example for usage with sentence_transformers.
 ```python
 from sentence_transformers import SentenceTransformer
+model = SentenceTransformer('Nehc/e5-large-ru')
 input_texts = ["passage: This is an example sentence", "passage: Каждый охотник желает знать.","query: Где сидит фазан?"]
 embeddings = model.encode(input_texts, normalize_embeddings=True)
 ```