29 lines
2.0 KiB
Markdown
29 lines
2.0 KiB
Markdown
# Text Generation Inference
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Text Generation Inference (TGI) is a toolkit for deploying and serving Large Language Models (LLMs). TGI enables high-performance text generation for the most popular open-source LLMs, including Llama, Falcon, StarCoder, BLOOM, GPT-NeoX, and T5.
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Text Generation Inference implements many optimizations and features, such as:
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- Simple launcher to serve most popular LLMs
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- Production ready (distributed tracing with Open Telemetry, Prometheus metrics)
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- Tensor Parallelism for faster inference on multiple GPUs
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- Token streaming using Server-Sent Events (SSE)
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- Continuous batching of incoming requests for increased total throughput
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- Optimized transformers code for inference using [Flash Attention](https://github.com/HazyResearch/flash-attention) and [Paged Attention](https://github.com/vllm-project/vllm) on the most popular architectures
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- Quantization with [bitsandbytes](https://github.com/TimDettmers/bitsandbytes) and [GPT-Q](https://arxiv.org/abs/2210.17323)
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- [Safetensors](https://github.com/huggingface/safetensors) weight loading
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- Watermarking with [A Watermark for Large Language Models](https://arxiv.org/abs/2301.10226)
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- Logits warper (temperature scaling, top-p, top-k, repetition penalty)
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- Stop sequences
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- Log probabilities
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- Custom Prompt Generation: Easily generate text by providing custom prompts to guide the model's output.
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- Fine-tuning Support: Utilize fine-tuned models for specific tasks to achieve higher accuracy and performance.
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Text Generation Inference is used in production by multiple projects, such as:
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- [Hugging Chat](https://github.com/huggingface/chat-ui), an open-source interface for open-access models, such as Open Assistant and Llama
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- [OpenAssistant](https://open-assistant.io/), an open-source community effort to train LLMs in the open
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- [nat.dev](http://nat.dev/), a playground to explore and compare LLMs.
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