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This article explores trends and tools for deploying large language models (LLMs) in on-premises environments. The authors believe that localized deployment is becoming increasingly important due to the needs of data privacy, cost control, and low latency.

The article summarizes a series of tools covering different needs from individual developers to enterprise-level: Ollama, LM Studio, Jan.AI, LocalAI and LLMOne.

This is a good starting point and overview for those considering how to implement LLMs on their own servers or devices.


Wow, this looks really cool.

What is the current support for OpenAI proxy or non-GPT models?

For example, using locally deployed Qwen models or LLaMA models.


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