MongoDB/mdbr-leaf-mt
feature-extraction model by MongoDB
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Model card & documentation
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mdbr-leaf-mt is a compact high-performance text embedding model designed for classification, clustering, semantic sentence similarity and summarization tasks. To enable even greater efficiency, mdbr-leaf-mt supports flexible asymmetric architectures and is robust to vector quantization and MRL truncation. If you are looking to perform semantic search / information retrieval (e.g. for RAGs), please check out our mdbr-leaf-ir model, which is specifically trained for these tasks. A technical report detailing our proposed LEAF training procedure is available here. The table below shows the scores for mdbr-leaf-mt on the MTEB v2 (English) benchmark, compared to other retrieval models. mdbr-leaf-mt ranks #1 on this benchmark for models with <30M parameters. See example output If you haven't already, you can install the Transformers.js JavaScript library from NPM using: You can then use the model to compute embeddings like this: See example output See here. mdbr-leaf-mt is aligned to mxbai-embed-large-v1, the model it has been distilled…
Read the full model card ↗ · Preview checked 2026-10-29T03:12:43.395Z
Inside the original model card — Document outline
- Content
- Introduction
- Technical Report
- Highlights
- Benchmark Comparison
- Quickstart
- Sentence Transformers
- Transformers.js
- Transformers Usage
- Asymmetric Retrieval Setup
- MRL Truncation
- Vector Quantization
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Documentation belongs to its respective authors. Reported project/model license: apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
MongoDB/mdbr-leaf-mt is a feature-extraction model repository published by MongoDB 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
- feature-extraction
- Library
- sentence-transformers
- Recent downloads (30 days)
- 93,544
- Cumulative likes
- 26
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 22,565,376
- Architecture
- BertModel
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2025-08-12T23:31:50.000Z
- Last modified
- 2026-07-20T23:25:19.000Z
Compatibility and lineage
Reported languages: en
Reported base models: microsoft/MiniLM-L6-v2
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 2026-10-24T06:49:26.940Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.