Model catalogue · Sentence-Transformers (offene Gewichte)
Mehrsprachiges Embedding
A small, multilingual embedding model for short pieces of text - subject lines, keywords, brief notes. Its very tight context window is the decisive limit: it is not made for whole file passages, but it is made for indexing a mixed-language corpus. It is procured via IONOS in the Berlin data centre; the German location is a property of the service there and not a setting that can be chosen wrongly. The chain for section 203 of the German Criminal Code is nevertheless not closed: the data processing agreement does contain a confidentiality undertaking expressly in awareness of criminal liability under section 203, but the product-specific confirmation for this service is still outstanding.
You can work with it - but part of the safeguard is open: either the provider does not commit to confidentiality itself, or it depends on an agreement you still have to conclude. Which of the two applies to which route is set out in the full matrix.
What it is good for
- Multilingual at very low resource requirements
- Available from German data centres, without a US group in the chain
- The most economical tier for indexing and short-text similarity
Where it stops
- 128 tokens of context - whole file passages do not fit
- For a file search across longer documents the larger embedding models in this catalogue are the right choice
- The product-specific confirmation of the section 203 clause for the AI Model Hub is still outstanding
Routes examined
The same model, procured differently, is a different legal position. What is examined per route is the contract chain, not the model.
| Route | Section 203 status | Version on this route |
|---|---|---|
| IONOS AI Model Hub (German data centres) | conditional | - |
The conditions behind a conditional status - which piece is open on which route and who closes it - are set out in the full matrix in the German catalogue, and we go through them in the conversation. The German page for Mehrsprachiges Embedding carries the sources with their retrieval dates.
Is Mehrsprachiges Embedding the right fit?
We go through your tasks and the route that carries them - and say plainly where it does not.
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