Higher performance OpenAI LLM service than vLLM serve: A pure C++ high-performance OpenAI LLM service implemented with GPRS+TensorRT-LLM+Tokenizers.cpp, supporting chat and function call, AI agents, distributed multi-GPU inference, multimodal capabilities, and a Gradio chat interface.

Deep Learning Deployment Framework: Supports tf/torch/trt/trtllm/vllm and other NN frameworks. Support dynamic batching, and streaming modes. It is dual-language compatible with Python and C++, offering scalability, extensibility, and high performance. It helps users quickly deploy models and provide services through HTTP/RPC interfaces.

TensorRT-LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and support state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT-LLM also contains components to create Python and C++ runtimes that orchestrate the inference execution in performant way.

Official code for "Heterogeneous Graph-based Framework with Disentangled Representations Learning for Multi-target Cross Domain Recommendation"

Official code for "Learning Positional Attention for Sequential Recommendation"

Official code for "Controllable Talking Face Generation by Implicit Facial Keypoints Editing"

【grps服务样例】包含c++、python自定义工程以及快捷部署样例。

【grps接入vllm】通过vllm LLMEngine Api实现LLM服务。

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