Text Generation Inference (TGI)

Text Generation Inference (TGI) is Hugging Face’s production-ready server for deploying and serving large language models with optimized performance and enterprise features.

Why It Matters

TGI provides a battle-tested solution for serving LLMs in production, used by Hugging Face’s own Inference Endpoints and many enterprise deployments. Key benefits:

• Production-ready: Docker-based deployment with health checks and metrics
• Optimized inference: Flash Attention, continuous batching, tensor parallelism
• Model ecosystem: Native support for Hugging Face model hub
• Enterprise features: Token streaming, stop sequences, grammar constraints
• Multi-GPU support: Serve large models across multiple GPUs

For AI engineers, TGI offers a well-documented path from prototype to production with minimal custom infrastructure.

Implementation Basics

Core features:

1. Continuous batching: Dynamically batch incoming requests for higher throughput
2. Flash Attention: Optimized attention computation for faster inference
3. Tensor parallelism: Distribute model across GPUs with Sharded flag
4. Quantization: Support for bitsandbytes, GPTQ, and AWQ formats
5. Prometheus metrics: Built-in observability for production monitoring

Docker deployment example:

docker run --gpus all \
  -p 8080:80 \
  ghcr.io/huggingface/text-generation-inference:latest \
  --model-id meta-llama/Llama-3-8B-Instruct

TGI integrates seamlessly with Hugging Face’s model hub, making it straightforward to serve any compatible model. The API supports both REST and gRPC, with OpenAI-compatible endpoints available for easy migration from cloud APIs.

Choose TGI when you need tight Hugging Face ecosystem integration or enterprise support options.