Rtp-Llm

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rtp-llm is a Coding & Development tool that provides a high-performance LLM inference engine. It is developed by Alibaba and supports diverse applications requiring efficient large language model deployment.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is rtp-llm?

RTP-LLM is Alibaba's high-performance LLM inference engine, designed to accelerate large language model deployment across various applications. It is widely utilized within Alibaba Group for services like Taobao, Tmall, and Cainiao. Key features include production-proven reliability, high performance achieved through advanced CUDA kernels like PagedAttention and FlashAttention, and support for WeightOnly INT8/INT4 Quantization. The engine offers flexibility with seamless integration for HuggingFace models, multi-LoRA service deployment, multimodal input handling, and multi-machine/multi-GPU tensor parallelism. It also incorporates advanced acceleration techniques such as Contextual Prefix Cache and Speculative Decoding, making it suitable for optimizing LLM inference in complex, high-demand environments.

Best used for

Ideal for developers who need to accelerate large language model inference, optimize GPU performance for LLMs, and deploy LLMs efficiently in production environments. Especially valuable for those working with diverse applications and requiring advanced acceleration techniques like quantization and caching.

Common actions

accelerate LLM inference

deploy large language models

optimize GPU performance

integrate HuggingFace models

face swappinggithub copilot"AI Agents"automated workflowcollaborationlow-code/no-codeopen-sourceworkflowsdeepfake

Capabilities

Key features

High-performance CUDA kernels
WeightOnly INT8/INT4 Quantization
HuggingFace model integration
Multimodal input support
Multi-GPU tensor parallelism
Contextual Prefix Cache
Speculative Decoding

Target Audience

developer

Integrations

hugging-face

Pricing & Plans

Open Source

Free

FAQs

What kind of hardware does RTP-LLM support?

RTP-LLM is currently optimized for V100 GPUs and has multi-hardware support in development for AMD ROCm, Intel CPU, and ARM CPU. It also supports Qwen series models and BERT embedding models on Yitian ARM CPU.

Does RTP-LLM support model quantization?

Yes, RTP-LLM supports WeightOnly INT8 Quantization with automatic quantization at load time, and WeightOnly INT4 Quantization using GPTQ and AWQ. It also features Adaptive KVCache Quantization for further optimization.

Can RTP-LLM handle multiple LoRA services?

Yes, RTP-LLM allows for the deployment of multiple LoRA services with a single model instance. This feature enhances flexibility and resource utilization for fine-tuned models.

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