#158 · Primary category： Inference & Local Deploy
aikit
🏗️ Fine-tune, build, and deploy open-source LLMs easily!
Project last updated：08/24/26
GitHub Stars
536
Forks
57
Contributors
10
License
MIT
Why we included this project
AIKit wraps the whole workflow of working with open LLMs into a single Docker-based tool, so a team can go from a raw model to a live, OpenAI-compatible endpoint without wiring together several services. Inference runs on LocalAI, which means any client that speaks the OpenAI API can talk to models like Llama or Mistral, and a declarative config file covers both serving and fine-tuning. The fine-tuning path uses Unsloth for fast, memory-efficient training, and models can be packaged as OCI artifacts and pushed through a standard container registry. For teams that want to self-host on their own hardware or in Kubernetes while keeping the option to adjust weights in place, that is a practical setup.
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