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Text Embeddings Inference - AI Model Serving Tool

Overview

Text Embeddings Inference is an open-source, high-performance toolkit from Hugging Face for deploying and serving text embeddings and sequence classification models. It provides dynamic batching, optimized transformer kernels (Flash Attention and cuBLASLt), support for multiple model types, and lightweight Docker images for fast inference.

Key Features

  • Deploy and serve text embeddings and sequence classification models
  • Dynamic batching for efficient throughput
  • Optimized transformer kernels using Flash Attention and cuBLASLt
  • Support for multiple model architectures and types
  • Lightweight Docker images for fast inference deployment

Ideal Use Cases

  • Production embedding generation for search and retrieval
  • Real-time similarity and semantic search pipelines
  • Batch embedding jobs for analytics and indexing
  • Sequence classification inference at scale
  • Model serving for NLP feature extraction

Getting Started

  • Clone the GitHub repository
  • Build or pull the provided lightweight Docker image
  • Configure the model and inference settings
  • Start the inference server
  • Send sample requests to validate embeddings

Pricing

No pricing information disclosed. Project repository is open-source.

Key Information

  • Category: Model Serving
  • Type: AI Model Serving Tool
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