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Copy file name to clipboardExpand all lines: README.md
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## Features Overview
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-**Model Preheat**: Models could be preloaded to clusters, to specified nodes to accelerate the model serving.
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-**Model Cache**: Models will be cached after downloading for faster model loading.
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-**Model Lifecycle Management**: Manage the model lifecycle automatically with different policies, like `Retain` or `Delete`.
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-**Model Hub Support**: Models could be downloaded directly from model hubs (Huggingface etc.) or object storages, no other efforts.
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-**Model Preheat**: Models could be preloaded to clusters, or specified nodes to accelerate the model serving.
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-**Model Cache**: Models will be cached as chunks after downloading for faster model loading.
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-**Model Lifecycle Management**: Model lifecycle is managed automatically with different strategies, like `Retain` or `Delete`.
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-**Plugin Framework**: _Filter_ and _Score_ plugins could be extended to pick up the best candidates.
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-**Memory Management(WIP)**: Manage the reserved memories for caching, together with LRU algorithm for GC.
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## You Should Know Before
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- Manta is not an all-in-one solution for model management, instead, it offers a lightweight solution to utilize the idle bandwidth and cost-effective disk, helping you save money.
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- It requires no additional components like databases or storage systems, simplifying setup and reducing effort.
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- All the models will be stored under the host path of `/mnt/models/`
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- After all, it's just a **cache system**.
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## Quick Start
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### Installation
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More details refer to the [APIs](https://github.com/InftyAI/Manta/blob/main/api/v1alpha1/torrent_types.go).
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