128-dimensional embeddings
According to the model card, the model maps sentences and paragraphs to a 128-dimensional dense vector space, matching the reported 128 pooling dimension.
Open Source Model Profile · sentence-transformers-testing
stsb-bert-tiny-safetensors
stsb-bert-tiny-safetensors is a 4.39M-parameter BERT-based sentence-similarity model from sentence-transformers-testing. Its model card documents 128-dimensional embeddings for clustering and semantic search.
- Publisher
- sentence-transformers-testing
- Task
- sentence-similarity
- Model type
- bert
- License
- Unknown
- Library
- sentence-transformers
- Publication status
- Accepted · not indexed
Model overview
stsb-bert-tiny-safetensors is published by sentence-transformers-testing as a sentence-similarity model. The captured configuration identifies BertModel with a bert model type, and Safetensors metadata reports 4,385,920 parameters. According to the model card, it is a sentence-transformers model that maps sentences and paragraphs to a 128-dimensional dense vector space.
Recorded capabilities
Mean-pooling configuration
The model card documents mean pooling over token embeddings with attention-mask averaging, and the architecture dump reports mean-token pooling as enabled.
Sentence-transformers and Transformers usage
According to the model card, it can be loaded with SentenceTransformer and encode, or with AutoTokenizer and AutoModel followed by pooling.
Documented training setup
According to the model card, training used a length-360 DataLoader, CosineSimilarityLoss, 10 epochs, and AdamW with a WarmupLinear schedule.
Use cases in the source record
- Clustering workflows that use the documented 128-dimensional sentence and paragraph vectors.
- Semantic-search experiments that use the model's sentence-level dense representations.
- Sentence-transformers encoding workflows that call the documented SentenceTransformer encode pattern.
Limitations and unknowns
- No evaluation results were extracted from this record.
- No license value was extracted from this record.
- No context-window value was extracted from this record.
- Provider state is historical snapshot data, not independently refreshed current availability.
Source and provenance
Source: sentence-transformers-testing/stsb-bert-tiny-safetensors
Captured: Unknown. Processed: 2026-09-07T19:34:57.645734+00:00.
sentence-transformers-testing/stsb-bert-tiny-safetensors This is a sentence-transformers model: It maps sentences & paragraphs to a 128 dimensional dense vector space and can be used for tasks like clustering or semantic search. Usage (Sentence-Transformers) Using this model becomes easy when you have sentence-transformers installed: pip install -U sentence-transformers Then you can use the model like this: from sentence_transformers import SentenceTransformer sentences = [ "This is an example sentence" , "Each sentence is converted" ] model = SentenceTransformer( 'sentence-transformers-testing/stsb-bert-tiny-safetensors' ) embeddin…
F001F002F003F004F005F006F007F009F010F011F012F013F014F015F016F017