Sentence Similarity
sentence-transformers
ONNX
Safetensors
English
bert
feature-extraction
entity-resolution
record-linkage
record-matching
data-matching
deduplication
arctic
snowflake-arctic-embed
lora
fine-tuned
Eval Results (legacy)
text-embeddings-inference
Instructions to use themelder/arctic-embed-xs-entity-resolution with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use themelder/arctic-embed-xs-entity-resolution with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("themelder/arctic-embed-xs-entity-resolution") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle