sentence-transformers/sentence-t5-base
sentence-similarity model by sentence-transformers
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Model card & documentation
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This is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space. The model works well for sentence similarity tasks, but doesn't perform that well for semantic search tasks. This model was converted from the Tensorflow model st5-base-1 to PyTorch. When using this model, have a look at the publication: Sentence-T5: Scalable sentence encoders from pre-trained text-to-text models. The tfhub model and this PyTorch model can produce slightly different embeddings, however, when run on the same benchmarks, they produce identical results. The model…
Read the full model card ↗ · Preview checked 2026-11-01T12:19:47.843Z
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Model overview
sentence-transformers/sentence-t5-base is a sentence-similarity model repository published by sentence-transformers on Hugging Face. The source reports the sentence-transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- sentence-similarity
- Library
- sentence-transformers
- Recent downloads (30 days)
- 130,020
- Cumulative likes
- 51
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 109,628,544
- Architecture
- T5EncoderModel
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2022-03-02T23:29:05.000Z
- Last modified
- 2025-03-06T13:39:02.000Z
Compatibility and lineage
Reported languages: en
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-01T06:54:31.802Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
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