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README.md
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- PartAI/TookaBERT-Base
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#
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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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The model is trained in two sizes: **
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## Usage
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from sentence_transformers import SentenceTransformer
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# Download from the 🤗 Hub
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model = SentenceTransformer("PartAI/
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# Run inference
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sentences = [
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'درنا از پرندگان مهاجر با پاهای بلند و گردن دراز است.',
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- `"متن: "` to documents
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| Model | #Params | Pair-Classification-Avg | Classification-Avg | Retrieval-Avg | Reranking-Avg |
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| [jina-embeddings-v3](https://huggingface.co/jinaai/jina-embeddings-v3) | 572M | 71.88 | **79.27** | 65.18
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| tooka-sbert-large-v2 | 353M | 80.24 | 74.73 | 59.80 | 73.44 | 72.05 |
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### Task-Specific Datasets in PTEB
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- PartAI/TookaBERT-Base
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# Tooka-SBERT-V2-Small
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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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The model is trained in two sizes: **Small** and **Large**
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## Usage
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from sentence_transformers import SentenceTransformer
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# Download from the 🤗 Hub
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model = SentenceTransformer("PartAI/Tooka-SBERT-V2-Small")
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# Run inference
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sentences = [
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'درنا از پرندگان مهاجر با پاهای بلند و گردن دراز است.',
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- `"متن: "` to documents
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| Model | #Params | Pair-Classification-Avg | Classification-Avg | Retrieval-Avg | Reranking-Avg | CrossTasks-Avg |
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|--------------------------------------------------------------------------------|:-------:|-------------------------|--------------------|---------------|---------------|----------------|
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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-Small](https://huggingface.co/PartAI/Tooka-SBERT-V2-Small) | 123M | 75.69 | 72.16 | 61.24 | 73.40 | 70.62 |
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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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| [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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| [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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### Task-Specific Datasets in PTEB
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