Model reference · open weights
deepset-mxbai-embed-de-large is an open-weight embedding model from mixedbread-ai, 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
mixedbread-ai/deepset-mxbai-embed-de-large-v1 This model is a powerful open-source German/English embedding model developed by Mixedbread in collaboration with deepset. It's built upon intfloat/multilingual-e5-large and trained using the AnglE loss. Read more details in our blog post. In a bread loaf: - State-of-the-art performance - Supports both binary quantization and Matryoshka Representation Learning (MRL). - Fine-tuned on 30+ million pairs of high-quality German data - Optimized for retrieval tasks - Supported Languages: German and English. - Requires a prompt: query: {query} for the query and passage: {doc} for the document Performance On the NDCG@10 metric, our model achieves an average performance of 51.7, setting a new standard for open-source German embedding models: In a case study with a legal data client, our model outperformed domain-specific alternatives: Binary Quantization and Matryoshka Our model supports both binary quantization and Matryoshka Representation Learning (MRL), allowing for significant efficiency gains: - Binary quantization: Retains 91.8% of performance while increasing efficiency by a factor of 32 - MRL: A 25% reduction in vector size still leaves 97.5% of model performance - At 512 dimensions, over 93% of model performance remains while cutting embedding sizes in half These optimizations can lead to substantial reductions in infrastructure costs for cloud computing and vector databases. Read more here. Quickstart Here are several ways to produce German sentence embeddings using our model. Note that you need to provide the prompt: query: {query} for the query and passage: {doc} for the document. API Reference Community Join our discord community or the Haystack community discord to share your feedback and thoughts. We're here to help and always happy to discuss the exciting field of machine learning! License Apache 2.0 Citation
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | mixedbread-ai |
|---|---|
| Type | Embedding models |
| Parameters (lead) | 487M |
| Context | 514 tokens |
| Variants | 1 |
| Runs with | sentence-transformers |
| Released | 2024-07-12 |
| Popularity | 123k downloads / month |
| Likes | 61 |
| Licence | Open weights |
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 |
|---|---|---|---|---|---|
| deepset-mxbai-embed-de-large-v1 | 487M | BF16 | ~1.1 GB | ✓ | Weights ↗ |
Using it via the API
Once AxForge deploys deepset-mxbai-embed-de-large for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (deepset-mxbai-embed-de-large 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":"deepset-mxbai-embed-de-large","input":"text to embed"}'
Licence
Open weights under apache-2.0 — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗
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