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pescn

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投稿

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1 ポイント·投稿者 pescn·11 か月前·0 コメント

[untitled]

1 ポイント·投稿者 pescn·12 か月前·0 コメント

Why I'm Convinced Enterprises Need Private LLM Deployment in 2025

pescn.medium.com
1 ポイント·投稿者 pescn·昨年·0 コメント

Large Language Model Deployment Tools You Need to Know in 2025

medium.com
3 ポイント·投稿者 pescn·昨年·1 コメント

Show HN: LLMOne – Deploy LLMs from bare metal to production in hours

github.com
5 ポイント·投稿者 pescn·昨年·0 コメント

コメント

pescn
·昨年·議論
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.
pescn
·昨年·議論
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.