facebookresearch/SentEval

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2110 stars · 307 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

SentEval is a Python library from Facebook Research for evaluating the quality of sentence embeddings via a suite of downstream transfer tasks and linguistic probing tasks. It helps researchers benchmark general-purpose fixed-size sentence representations.

Use cases

• evaluate quality of my sentence embeddings
• benchmark sentence encoders on downstream NLP tasks
• test what linguistic properties my sentence representations encode
• compare sentence embeddings on semantic textual similarity
• run standard NLP evaluation benchmarks like SNLI and STS

When to choose

• you need standardized benchmarks for sentence embedding quality
• you are researching general-purpose sentence representations
• you want probing tasks to analyze linguistic information in embeddings

When to avoid

• you need to generate or train embeddings rather than evaluate them
• you need actively maintained tooling with recent NLP benchmarks
• you are not working in Python with PyTorch

Facets

library · maturity maintenance

machine-learning nlp benchmarking testing machine-learning python sentence-embeddings evaluation-toolkit transfer-tasks probing-tasks pytorch research natural-language-processing linux macos

Member repositories

For agents

markdown · JSON · MCP: product_card(name="facebookresearch/SentEval")