princeton-nlp/SimCSE

Health v2 · maintenance only

Adoption not part of the score

3654 stars · 536 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

SimCSE is a Python library and research codebase implementing simple contrastive learning for sentence embeddings, with pre-trained unsupervised and supervised models. It provides an easy-to-use sentence embedding tool compatible with Hugging Face Transformers.

Use cases

• encode sentences into embeddings
• compute sentence similarity
• train custom sentence embedding models with contrastive learning
• evaluate sentence embeddings on STS benchmarks
• use pretrained sentence embeddings for semantic search

When to choose

• you need high-quality sentence embeddings from a well-cited research model
• you want to train or fine-tune sentence embeddings with contrastive learning
• you want a simple pip-installable embedding tool

When to avoid

• you need actively developed features or recent model architectures
• you need multilingual embeddings out of the box
• you need a production embedding service rather than a research library

Facets

library · maturity maintenance

nlp machine-learning deep-learning machine-learning deep-learning python sentence-embeddings contrastive-learning pretrained-models research natural-language-processing

Member repositories

For agents

markdown · JSON · MCP: product_card(name="princeton-nlp/SimCSE")