Alibaba-NLP/gte-multilingual-base
sentence-similarity model by Alibaba-NLP
From the publisher
Model card & documentation
Source previewRead the publisher’s intended use, setup instructions, evaluations and limitations. The original model card is the source of truth.
The gte-multilingual-base model is the latest in the GTE (General Text Embedding) family of models, featuring several key attributes: Paper: mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrieval refer to enable-unpadding-and-xformers. Usage via docker and infinity, MIT Licensed. Usage via Docker and Text Embeddings Inference (TEI): Then you can send requests to the deployed API via the OpenAI-compatible v1/embeddings route (more information about the OpenAI Embeddings API): We validated the performance of the gte-multilingual-base model on multiple downstream tasks, including multilingual retrieval, cross-lingual retrieval, long text retrieval, and general text representation evaluation on the MTEB Leaderboard, among others. Retrieval results on MIRACL and MLDR…
Read the full model card ↗ · Preview checked 2026-10-30T03:26:26.156Z
Inside the original model card — Document outline
- gte-multilingual-base
- Model Information
- Usage
- Get Dense Embeddings with Transformers
- Use with sentence-transformers
- Use with infinity
- Use with Text Embeddings Inference (TEI)
- Use with custom code to get dense embeddings and sparse token weights
- Evaluation
- Retrieval Task
- MTEB
- Cloud API Services
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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-multilingual-base is a sentence-similarity model repository published by Alibaba-NLP 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
- sentence-similarity
- Library
- sentence-transformers
- Recent downloads (30 days)
- 981,220
- Cumulative likes
- 390
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 305,369,089
- Architecture
- NewModel, NewForTokenClassification
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2024-07-20T08:37:28.000Z
- Last modified
- 2025-07-05T01:38:16.000Z
Compatibility and lineage
Reported languages: af, ar, az, be, bg, bn, ca, ceb, cs, cy, da, de, el, en, es, et, eu, fa, fi, fr, gl, gu, he, hi, hr, ht, hu, hy, id, is, it, ja, jv, ka, kk, km, kn, ko, ky, lo
Base-model lineage was not included.
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
Check license terms and access requirements first. Review the model card’s documented loading instructions, evaluations and safety limitations. Benchmark scores are not imported by this directory, and popularity is not an accuracy ranking.
No model weights are downloaded or executed by AltAPIs. Never enable remote model code without reviewing it.
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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