nicher92/saga-embed_v1

General information

This is a ScAndinavian GenerAl embedding model (SAGA).

Usage

This model uses custom prompts for different tasks to achieve optimal performance. For standard inference, format your prompts as follows:

• Retrieval (Queries): task: retrieval | query: {text}
• Retrieval (Passages): title: none | text: {text}
• Clustering: task: clustering | query: {text}
• Classification: task: classification | query: {text}
• Semantic Similarity: task: semantic similarity | query: {text}

from sentence_transformers import SentenceTransformer

model = SentenceTransformer("nicher92/saga_embed_v1")

# Example: Encoding a search query
query = "task: retrieval | query: Hur mycket skatt betalar jag i Sverige?"
embedding = model.encode(query)

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Link to technical report