Feature Extraction
sentence-transformers
Safetensors
sparse-encoder
sparse
asymmetric
inference-free
splade
Generated from Trainer
dataset_size:46954
loss:CachedSpladeLoss
loss:SparseMultipleNegativesRankingLoss
loss:FlopsLoss
Eval Results (legacy)
Instructions to use yjoonjang/reviewsearch-sparse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use yjoonjang/reviewsearch-sparse with sentence-transformers:
from sentence_transformers import SparseEncoder model = SparseEncoder("yjoonjang/reviewsearch-sparse") 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: 108 Bytes
97c1846 | 1 2 3 4 5 | {
"pooling_strategy": "max",
"activation_function": "log1p_relu",
"embedding_dimension": 30522
} |