Feature Extraction
sentence-transformers
Safetensors
Korean
English
milco
sparse-encoder
sparse
splade
learned-sparse-retrieval
custom_code
Instructions to use nlpai-lab/KURE-Sparse-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use nlpai-lab/KURE-Sparse-base with sentence-transformers:
from sentence_transformers import SparseEncoder model = SparseEncoder("nlpai-lab/KURE-Sparse-base", trust_remote_code=True) queries = ["Which planet is known as the Red Planet?"] documents = [ "Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", ] query_embeddings = model.encode_query(queries) document_embeddings = model.encode_document(documents) similarities = model.similarity(query_embeddings, document_embeddings) print(similarities) - Notebooks
- Google Colab
- Kaggle
File size: 100 Bytes
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{
"idx": 0,
"name": "0",
"path": "",
"type": "milco_encoder.MilcoDualView"
}
] |