📄 中文摘要
在设备上运行大型语言模型（LLM）变得越来越可行。通过直接在硬件上运行模型，可以提高隐私性并减少对网络的依赖，而无需将提示发送到云 API。使用 picoLLM 推理引擎，可以在 Python 中轻松实现 LLM 的运行。首先，需要安装相应的 Python 包，然后从 Picovoice 控制台获取 AccessKey 和下载模型文件。通过创建账户并下载模型，用户可以开始在本地设备上进行 LLM 推理。
在设备上运行 LLM 推理的 Python 实践
出处: Trying On-Device LLM Inference with Python
发布: 2026年2月17日
📄 English Summary
Trying On-Device LLM Inference with Python
Running large language models (LLMs) on-device is becoming increasingly feasible. By executing models directly on hardware, privacy is enhanced and reliance on network connectivity is reduced, eliminating the need to send prompts to a cloud API. Using the picoLLM inference engine, LLMs can be easily run in Python. First, the necessary Python package must be installed, followed by obtaining an AccessKey and downloading a model file from the Picovoice Console. By creating an account and downloading models, users can initiate LLM inference on their local devices.