Sentence Similarity
sentence-transformers
Safetensors
Hebrew
hebrew
semantic-retrieval
information-retrieval
dense-retrieval
reranking
ensemble
competition
Instructions to use HebArabNlpProject/Semantic-Retrieval-1st-place with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use HebArabNlpProject/Semantic-Retrieval-1st-place with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("HebArabNlpProject/Semantic-Retrieval-1st-place") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
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# Hebrew Semantic Retrieval — 1st Place Solution
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**Competition:**
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**Result:** 🥇 **1st place** — nDCG@20 = **0.6736** (private test set)
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# Hebrew Semantic Retrieval — 1st Place Solution
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**Competition:** Hebrew Semantic Retrieval Challenge by MAFAT DDR&D (Directorate of Defense Research & Development) in partnership with the **Israel National NLP Program**
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**Result:** 🥇 **1st place** — nDCG@20 = **0.6736** (private test set)
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