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Universal LLM Deployment Engine with ML Compilation

17 pointsby ruihangl12 months ago

7 comments

zhye12 months ago
Glad to see MLC is becoming more mature :) I can imagine the unified engine could help build agents on multiple devices.<p>Any ideas on how those edge and cloud models collaborate on compound tasks (e.g. the compound ai systems: <a href="https:&#x2F;&#x2F;bair.berkeley.edu&#x2F;blog&#x2F;2024&#x2F;02&#x2F;18&#x2F;compound-ai-systems&#x2F;" rel="nofollow">https:&#x2F;&#x2F;bair.berkeley.edu&#x2F;blog&#x2F;2024&#x2F;02&#x2F;18&#x2F;compound-ai-system...</a>)
ruihangl12 months ago
A unified efficient open-source LLM deployment engine for both cloud server and local use cases.<p>It comes with full OpenAI-compatible API that runs directly with Python, iOS, Android, browsers. Supporting deploying latest large language models such as Qwen2, Phi3, and more.
yongwww12 months ago
The MLCEngine presents an approach to universal LLM deployment, glad to know it works for both local servers and cloud devices with competitive performance. Looking forward to exploring it further!
neetnestor12 months ago
Looks cool. I&#x27;m looking forward to trying building some interesting apps using the SDKs.
CharlieRuan12 months ago
From first-hand experience, the all-in-one framework really helps reduce engineering effort!
cyx612 months ago
AI ALL IN ONE! Super universal and performant!
crowwork12 months ago
runs on qwen2 on iphone with 26 tok&#x2F;sec and a OpenAI style swift API