Feature Extraction
sentence-transformers
Safetensors
Spanish
English
bert
sparse-encoder
splade
sparse
spanish
english
retrieval
text-embeddings-inference
Eval Results (legacy)
Instructions to use alrolo3/splade-v3-spanish-vllm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use alrolo3/splade-v3-spanish-vllm with sentence-transformers:
from sentence_transformers import SparseEncoder model = SparseEncoder("alrolo3/splade-v3-spanish-vllm") 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
Commit History
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Remove duplicate mlm_head tensors for vLLM compatibility
Verified signatureKeep the canonical cls.predictions tensors and remove only the six bitwise-duplicate mlm_head tensors. SparseEncoder query/document outputs were validated as exactly identical before and after cleanup.6a50839
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Improve model card README
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Upload SPLADE v3 Spanish model
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initial commit
Verified signature765e599