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# SentenceTransformer based on aloobun/d-mxbai-L8-embed
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This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [aloobun/d-mxbai-L8-embed](https://huggingface.co/aloobun/d-mxbai-L8-embed) on the [en-mr](https://huggingface.co/datasets/aloobun/indic-parallel-sentences-talks), [en-hi](https://huggingface.co/datasets/aloobun/indic-parallel-sentences-talks), [en-bn](https://huggingface.co/datasets/aloobun/indic-parallel-sentences-talks), [en-gu](https://huggingface.co/datasets/aloobun/indic-parallel-sentences-talks), [en-ta](https://huggingface.co/datasets/aloobun/indic-parallel-sentences-talks), [en-kn](https://huggingface.co/datasets/aloobun/indic-parallel-sentences-talks), [en-te](https://huggingface.co/datasets/aloobun/indic-parallel-sentences-talks) and [en-ml](https://huggingface.co/datasets/aloobun/indic-parallel-sentences-talks) datasets. It maps sentences & paragraphs to a 1024-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
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## Model Details
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# SentenceTransformer based on aloobun/d-mxbai-L8-embed
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This is a [sentence-transformers](https://www.SBERT.net) model finetuned (to extend a monolingual model to several indic languages) from [aloobun/d-mxbai-L8-embed](https://huggingface.co/aloobun/d-mxbai-L8-embed) on the [en-mr](https://huggingface.co/datasets/aloobun/indic-parallel-sentences-talks), [en-hi](https://huggingface.co/datasets/aloobun/indic-parallel-sentences-talks), [en-bn](https://huggingface.co/datasets/aloobun/indic-parallel-sentences-talks), [en-gu](https://huggingface.co/datasets/aloobun/indic-parallel-sentences-talks), [en-ta](https://huggingface.co/datasets/aloobun/indic-parallel-sentences-talks), [en-kn](https://huggingface.co/datasets/aloobun/indic-parallel-sentences-talks), [en-te](https://huggingface.co/datasets/aloobun/indic-parallel-sentences-talks) and [en-ml](https://huggingface.co/datasets/aloobun/indic-parallel-sentences-talks) datasets. It maps sentences & paragraphs to a 1024-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
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WIP
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## Model Details
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