Model reference · open weights
stsb-bert-tiny-safetensors is an open-weight embedding model from sentence-transformers-testing, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.
About
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: Then you can use the model like this: Usage (HuggingFace Transformers) Without sentence-transformers, you can use the model like this: First, you pass your input through the transformer model, then you have to apply the right pooling-operation on-top of the contextualized word embeddings. Evaluation Results For an automated evaluation of this model, see the Sentence Embeddings Benchmark: https://seb.sbert.net Training The model was trained with the parameters: DataLoader: torch.utils.data.dataloader.DataLoader of length 360 with parameters: Loss: sentencetransformers.losses.CosineSimilarityLoss.CosineSimilarityLoss Parameters of the fit()-Method: Full Model Architecture Citing & Authors
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | sentence-transformers-testing |
|---|---|
| Type | Embedding models |
| Parameters (lead) | 4M |
| Context | 512 tokens |
| Variants | 1 |
| Runs with | sentence-transformers |
| Released | 2023-11-06 |
| Popularity | 2M downloads / month |
| Likes | 4 |
| Licence | Commercial licence needed |
How it works
Variants
Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.
| Variant | Params | Precision | VRAM | Fits 16 GB | Weights |
|---|---|---|---|---|---|
| stsb-bert-tiny-safetensors | 4M | BF16 | ~0 GB | ✓ | Weights ↗ |
Using it via the API
Once AxForge deploys stsb-bert-tiny-safetensors for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (stsb-bert-tiny-safetensors below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/embeddings \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"stsb-bert-tiny-safetensors","input":"text to embed"}'
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Licence
The weights are open but its licence needs a commercial agreement for business use. AxForge can arrange that licence and host the model for you — you pay AxForge, we settle with the model’s maker. Ask us for a quote. Read the licence ↗
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