Sentence Similarity
sentence-transformers
Safetensors
Hebrew
hebrew
semantic-retrieval
information-retrieval
dense-retrieval
reranking
bge-m3
competition
Instructions to use HebArabNlpProject/Semantic-Retrieval-3rd-place with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use HebArabNlpProject/Semantic-Retrieval-3rd-place with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("HebArabNlpProject/Semantic-Retrieval-3rd-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
Download models/test_encoder_only_base_bge_m3_new1/model.safetensors from HebArabNlpProject/Semantic-Retrieval-3rd-place: direct link, hf CLI and curl.
- Browser
- Download file 1.14 GB
-
https://huggingface.co/HebArabNlpProject/Semantic-Retrieval-3rd-place/resolve/main/models/test_encoder_only_base_bge_m3_new1/model.safetensors
- Command line
-
hf download hf://HebArabNlpProject/Semantic-Retrieval-3rd-place/models/test_encoder_only_base_bge_m3_new1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/HebArabNlpProject/Semantic-Retrieval-3rd-place/resolve/main/models/test_encoder_only_base_bge_m3_new1/model.safetensors
1.14 GB
- Xet hash:
- c0c1eb89fd184ae7f1b702250e961bacca50b7178a57248361404917c869033f
- Size of remote file:
- 1.14 GB
- SHA256:
- 86993a0584e46bd11ed8dfa406fe270a4ebdaaaf9e39ccb5e317625ee955a6ca
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