metadata
title: README
emoji: 🐢
colorFrom: purple
colorTo: purple
sdk: static
pinned: false
Text-Generation-Inference is a solution build for deploying and serving Large Language Models (LLMs). TGI enables high-performance text generation using Tensor Parallelism and dynamic batching for the most popular open-source LLMs, including StarCoder, BLOOM, GPT-NeoX, Llama, and T5. Text Generation Inference is already used by customers such as IBM, Grammarly, and the Open-Assistant initiative implements optimization for all supported model architectures, including:
- Tensor Parallelism and custom cuda kernels
- Optimized transformers code for inference using flash-attention and Paged Attention on the most popular architectures
- Quantization with bitsandbytes or gptq
- Continuous batching of incoming requests for increased total throughput
- Accelerated weight loading (start-up time) with safetensors
- Logits warpers (temperature scaling, topk, repetition penalty ...)
- Watermarking with A Watermark for Large Language Models
- Stop sequences, Log probabilities
- Token streaming using Server-Sent Events (SSE)
Currently optimized architectures
Check out the source code 👉
- the server backend: https://github.com/huggingface/text-generation-inference
- the Chat UI: https://huggingface.co/spaces/text-generation-inference/chat-ui