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README.md
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@@ -47,19 +47,35 @@ More details on the dataset, models, and baseline results can be found in our [p
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Other Monolingual similarity models are listed below: <br>
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<a href='https://huggingface.co/l3cube-pune/marathi-sentence-similarity-sbert'> Marathi </a> <br>
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<a href='https://huggingface.co/l3cube-pune/hindi-sentence-similarity-sbert'> Hindi </a> <br>
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<a href='https://huggingface.co/l3cube-pune/kannada-sentence-similarity-sbert'> Kannada </a> <br>
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<a href='https://huggingface.co/l3cube-pune/telugu-sentence-similarity-sbert'> Telugu </a> <br>
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<a href='https://huggingface.co/l3cube-pune/malayalam-sentence-similarity-sbert'> Malayalam </a> <br>
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<a href='https://huggingface.co/l3cube-pune/tamil-sentence-similarity-sbert'> Tamil </a> <br>
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<a href='https://huggingface.co/l3cube-pune/gujarati-sentence-similarity-sbert'> Gujarati </a> <br>
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<a href='https://huggingface.co/l3cube-pune/odia-sentence-similarity-sbert'> Oriya </a> <br>
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<a href='https://huggingface.co/l3cube-pune/bengali-sentence-similarity-sbert'> Bengali </a> <br>
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<a href='https://huggingface.co/l3cube-pune/punjabi-sentence-similarity-sbert'> Punjabi </a> <br>
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<a href='https://
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This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
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```
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<a href='https://arxiv.org/abs/2211.11187'> monolingual Indic SBERT paper </a> <br>
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<a href='https://arxiv.org/abs/2304.11434'> multilingual Indic SBERT paper </a>
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Other Monolingual similarity models are listed below: <br>
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<a href='https://huggingface.co/l3cube-pune/marathi-sentence-similarity-sbert'> Marathi Similarity </a> <br>
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<a href='https://huggingface.co/l3cube-pune/hindi-sentence-similarity-sbert'> Hindi Similarity </a> <br>
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<a href='https://huggingface.co/l3cube-pune/kannada-sentence-similarity-sbert'> Kannada Similarity </a> <br>
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<a href='https://huggingface.co/l3cube-pune/telugu-sentence-similarity-sbert'> Telugu Similarity </a> <br>
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<a href='https://huggingface.co/l3cube-pune/malayalam-sentence-similarity-sbert'> Malayalam Similarity </a> <br>
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<a href='https://huggingface.co/l3cube-pune/tamil-sentence-similarity-sbert'> Tamil Similarity </a> <br>
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<a href='https://huggingface.co/l3cube-pune/gujarati-sentence-similarity-sbert'> Gujarati Similarity </a> <br>
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<a href='https://huggingface.co/l3cube-pune/odia-sentence-similarity-sbert'> Oriya Similarity </a> <br>
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<a href='https://huggingface.co/l3cube-pune/bengali-sentence-similarity-sbert'> Bengali Similarity </a> <br>
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<a href='https://huggingface.co/l3cube-pune/punjabi-sentence-similarity-sbert'> Punjabi Similarity </a> <br>
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<a href='https://huggingface.co/l3cube-pune/indic-sentence-similarity-sbert'> Indic Similarity (multilingual)</a> <br>
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Other Monolingual Indic sentence BERT models are listed below: <br>
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<a href='https://huggingface.co/l3cube-pune/marathi-sentence-bert-nli'> Marathi SBERT</a> <br>
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<a href='https://huggingface.co/l3cube-pune/hindi-sentence-bert-nli'> Hindi SBERT</a> <br>
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<a href='https://huggingface.co/l3cube-pune/kannada-sentence-bert-nli'> Kannada SBERT</a> <br>
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<a href='https://huggingface.co/l3cube-pune/telugu-sentence-bert-nli'> Telugu SBERT</a> <br>
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<a href='https://huggingface.co/l3cube-pune/malayalam-sentence-bert-nli'> Malayalam SBERT</a> <br>
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<a href='https://huggingface.co/l3cube-pune/tamil-sentence-bert-nli'> Tamil SBERT</a> <br>
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<a href='https://huggingface.co/l3cube-pune/gujarati-sentence-bert-nli'> Gujarati SBERT</a> <br>
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<a href='https://huggingface.co/l3cube-pune/odia-sentence-bert-nli'> Oriya </a> SBERT<br>
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<a href='https://huggingface.co/l3cube-pune/bengali-sentence-bert-nli'> Bengali SBERT</a> <br>
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<a href='https://huggingface.co/l3cube-pune/punjabi-sentence-bert-nli'> Punjabi SBERT</a> <br>
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<a href='https://huggingface.co/l3cube-pune/punjabi-sentence-bert-nli'> Indic SBERT (multilingual)</a> <br>
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This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
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