Sentence Similarity
sentence-transformers
Safetensors
Persian
bert
feature-extraction
loss:CachedMultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use PartAI/Tooka-SBERT-V2-Large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use PartAI/Tooka-SBERT-V2-Large with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("PartAI/Tooka-SBERT-V2-Large") sentences = [ "درنا از پرندگان مهاجر با پاهای بلند و گردن دراز است.", "درناها با قامتی بلند و بالهای پهن، از زیباترین پرندگان مهاجر به شمار میروند.", "درناها پرندگانی کوچک با پاهای کوتاه هستند که مهاجرت نمیکنند.", "ایران برای بار دیگر توانست به مدال طلا دست یابد." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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This model is a Sentence Transformers model trained for semantic textual similarity and embedding tasks. It maps sentences and paragraphs to a dense vector space, where semantically similar texts are close together.
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| [multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base) | 278M | 70.76 | 69.71 | 63.90 | **76.01** | 70.09 |
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| [jina-embeddings-v3](https://huggingface.co/jinaai/jina-embeddings-v3) | 572M | 71.88 | **79.27** | **65.18** | 64.62 | 70.24 |
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| [Tooka-SBERT-V1-Large](https://huggingface.co/PartAI/Tooka-SBERT) | 353M | **81.52** | 71.54 | 45.61 | 60.44 | 64.78 |
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| [tooka-sbert-base-v2](https://huggingface.co/PartAI/Tooka-SBERT-V2-Small) | 123M | 75.69 | 72.16 | 61.24 | 73.40 | 70.62 |
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| [Tooka-SBERT-V2-Large](https://huggingface.co/PartAI/Tooka-SBERT-V2-Large) | 353M | 80.24 | 74.73 | 59.80 | 73.44 | **72.05** |
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# Tooka-SBERT-V2-Large
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This model is a Sentence Transformers model trained for semantic textual similarity and embedding tasks. It maps sentences and paragraphs to a dense vector space, where semantically similar texts are close together.
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| [multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base) | 278M | 70.76 | 69.71 | 63.90 | **76.01** | 70.09 |
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| [jina-embeddings-v3](https://huggingface.co/jinaai/jina-embeddings-v3) | 572M | 71.88 | **79.27** | **65.18** | 64.62 | 70.24 |
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| [Tooka-SBERT-V1-Large](https://huggingface.co/PartAI/Tooka-SBERT) | 353M | **81.52** | 71.54 | 45.61 | 60.44 | 64.78 |
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| [Tooka-SBERT-V2-Small](https://huggingface.co/PartAI/Tooka-SBERT-V2-Small) | 123M | 75.69 | 72.16 | 61.24 | 73.40 | 70.62 |
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| [Tooka-SBERT-V2-Large](https://huggingface.co/PartAI/Tooka-SBERT-V2-Large) | 353M | 80.24 | 74.73 | 59.80 | 73.44 | **72.05** |
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