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yahyaabd
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bps-indosbert-base-p2

Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
text-embeddings-inference
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  1. README.md +3 -4
  2. added_tokens.json +97 -0
  3. config.json +1 -1
  4. model.safetensors +2 -2
  5. special_tokens_map.json +35 -5
  6. tokenizer.json +855 -0
  7. tokenizer_config.json +760 -0
README.md CHANGED
@@ -3,20 +3,19 @@ tags:
3
  - sentence-transformers
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  - sentence-similarity
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  - feature-extraction
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- base_model: indobenchmark/indobert-base-p2
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  pipeline_tag: sentence-similarity
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  library_name: sentence-transformers
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  ---
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- # SentenceTransformer based on indobenchmark/indobert-base-p2
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- This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [indobenchmark/indobert-base-p2](https://huggingface.co/indobenchmark/indobert-base-p2). It maps sentences & paragraphs to a 768-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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  ### Model Description
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  - **Model Type:** Sentence Transformer
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- - **Base model:** [indobenchmark/indobert-base-p2](https://huggingface.co/indobenchmark/indobert-base-p2) <!-- at revision 94b4e0a82081fa57f227fcc2024d1ea89b57ac1f -->
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  - **Maximum Sequence Length:** 512 tokens
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  - **Output Dimensionality:** 768 dimensions
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  - **Similarity Function:** Cosine Similarity
 
3
  - sentence-transformers
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  - sentence-similarity
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  - feature-extraction
 
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  pipeline_tag: sentence-similarity
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  library_name: sentence-transformers
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  ---
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+ # SentenceTransformer
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+ This is a [sentence-transformers](https://www.SBERT.net) model trained. It maps sentences & paragraphs to a 768-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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  ### Model Description
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  - **Model Type:** Sentence Transformer
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+ <!-- - **Base model:** [Unknown](https://huggingface.co/unknown) -->
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  - **Maximum Sequence Length:** 512 tokens
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  - **Output Dimensionality:** 768 dimensions
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  - **Similarity Function:** Cosine Similarity
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297
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303
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328
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329
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415
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417
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423
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424
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425
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429
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431
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433
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439
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495
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496
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503
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511
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513
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800
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801
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802
  }
803
  },
804
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