Alibaba-NLP/gte-modernbert-base
sentence-similarity model by Alibaba-NLP
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Model card & documentation
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We are excited to introduce the gte-modernbert series of models, which are built upon the latest modernBERT pre-trained encoder-only foundation models. The gte-modernbert series models include both text embedding models and rerank models. The gte-modernbert models demonstrates competitive performance in several text embedding and text retrieval evaluation tasks when compared to similar-scale models from the current open-source community. This includes assessments such as MTEB, LoCO, and COIR evaluation. Use with transformers Use with sentence-transformers: Use with transformers.js: Additionally, you can also deploy Alibaba-NLP/gte-modernbert-base with Text Embeddings Inference (TEI) as follows: Then you can send requests to the deployed API via the OpenAI-compatible v1/embeddings route (more information about the OpenAI Embeddings API): The gte-modernbert series of models follows the training scheme of the previous GTE models, with the only difference being that the pre-training language model base has been replaced from GTE-MLM to ModernBert. For more training details, please refer to…
Read the full model card ↗ · Preview checked 2026-10-27T14:50:33.845Z
Inside the original model card — Document outline
- gte-modernbert-base
- Model Overview
- Model list
- Usage
- Training Details
- Evaluation
- MTEB
- LoCo (Long Document Retrieval)(NDCG@10)
- COIR (Code Retrieval Task)(NDCG@10)
- BEIR(NDCG@10)
- Hiring
- Citation
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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
Alibaba-NLP/gte-modernbert-base is a sentence-similarity model repository published by Alibaba-NLP on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- sentence-similarity
- Library
- transformers
- Recent downloads (30 days)
- 142,623
- Cumulative likes
- 204
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 149,014,272
- Architecture
- ModernBertModel
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2025-01-20T03:03:48.000Z
- Last modified
- 2025-07-04T10:03:26.000Z
Compatibility and lineage
Reported languages: en
Reported base models: answerdotai/ModernBERT-base
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 2026-11-01T06:54:31.802Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
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