Inference
Speeding Up Model Inference with TensorRT
· ☕ 4 min read
1. What Is TensorRT TensorRT is a C++ library mainly used for high-performance inference acceleration on NVIDIA GPUs. It provides both a C++ API and a Python API for integration. The mainstream deep learning frameworks TensorRT supports are: Caffe, where TensorRT can read the prototxt format directly TensorFlow, where the

Large Model Inference with Triton Server and TensorRT-LLM in a Container
· ☕ 5 min read
1. Compiling Models with TensorRT-LLM 1.1 Introduction to TensorRT-LLM When using TensorRT, you usually need to convert the model to ONNX format, then convert the ONNX to TensorRT format, and finally run inference in TensorRT or Triton Server. But this conversion process is not simple, and you often run into

Running llama-Architecture LLMs on CPU
· ☕ 5 min read
1. Running Locally in Containers Start the LLM 1 docker run --security-opt apparmor=unconfined --security-opt seccomp=unconfined --rm -p 8000:8000 shaowenchen/chinese-alpaca-2-7b-gguf:Q2_K The API documentation is available at http://localhost:8000/docs, as shown below: Deploy a simple Chat UI Note that the OPENAI_API_HOST parameter must be set to your host machine’s IP address rather than localhost or 127.

LLM Deployment Tool llama.cpp
· ☕ 5 min read
1. LLM Deployment Tool llama.cpp Research on large models is split into two parts: training and inference. The training process is essentially the process of finding model parameters that minimize the model’s loss function and optimize the inference results. Once training is complete, the model’s parameters are fixed, and at