Inference
Running llama-Architecture LLMs on CPU
· β˜• 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
· β˜• 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