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github.com/huggingface/text-embeddings-inference
AI Infrastructure & MLOps
Open-source projectOpen source
Hugging Face Text Embeddings Inference serves text embedding models through an inference solution.
About text-embeddings-inference
Text Embeddings Inference (TEI) is an open source toolkit for deploying and serving text embedding models and sequence classification models. The project's homepage says it supports high-performance extraction for popular embedding models, including FlagEmbedding, Ember, GTE and E5.
The homepage lists supported model families, including Nomic, BERT, CamemBERT, XLM-RoBERTa, JinaBERT, Mistral, Alibaba GTE, Qwen2, MPNet, ModernBERT, Qwen3 and Gemma3. Sequence classification and re-ranking support is listed separately and is limited to CamemBERT and XLM-RoBERTa sequence classification models with absolute positions. Some listed models are marked as gated, which indicates access restrictions apply to them. The benchmark on the homepage covers one model on one NVIDIA A10 GPU, so its performance figures apply only to that setup.
Key features
- Serves open source text embedding and sequence classification models
- Token-based dynamic batching for inference requests
- Optimized transformers code using Flash Attention, Candle and cuBLASLt
- Loads model weights in Safetensors and ONNX formats
- Metal support for running locally on Macs
- Distributed tracing with OpenTelemetry and Prometheus metrics
Best for: Developers and machine learning teams who need to deploy and serve open source text embedding or re-ranking models for inference.
Good for
- Open source project with a public GitHub repository
- Supports a range of embedding model families listed on the homepage
- Includes production-oriented features such as Prometheus metrics and OpenTelemetry tracing
Watch out for
- The homepage says it currently supports only the listed model architectures
- Some listed models are gated and require access
- Benchmark figures are reported for one model on one GPU setup
text-embeddings-inference at a glance
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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text-embeddings-inference FAQ
Which types of models does it support?
It supports text embedding models from several listed families. For sequence classification and re-ranking, it currently supports CamemBERT and XLM-RoBERTa sequence classification models with absolute positions.
Can it run on a Mac?
The homepage states that it includes Metal support for local execution on Macs.
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