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massive thank you to [@silveroxides](https://huggingface.co/silveroxides) for phenomenal work collecting pristine state dicts and related information
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#
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# MIR (Machine Intelligence Resource)
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#
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MIR is a naming standard, a proposed schema for ML work.<br>
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In its current incarnation, it looks like this:
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```
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and the super-resolution registry code from [Spandrel](https://github.com/chaiNNer-org/spandrel/blob/main/libs/spandrel/spandrel/__helpers/registry.py) library.
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## Goals
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- Standard identification scheme for all ML-related development
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- Simplification of code for model-related logistics
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- Rapid retrieval of resources and metadata
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- Efficient and reliable compatability checks
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massive thank you to [@silveroxides](https://huggingface.co/silveroxides) for phenomenal work collecting pristine state dicts and related information
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#
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> [!IMPORTANT]
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> # MIR (Machine Intelligence Resource)
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MIR is a naming standard, a proposed schema for ML work.<br>
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In its current incarnation, it looks like this:
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> [!NOTE]
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> # mir : model . transformer . clip-l : stable-diffusion-xl
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```
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mir : model . lora . hyper : flux-1
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↑ ↑ ↑ ↑ ↑
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mir:[domain].[architecture].[implementation]:[compatibility]
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```
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This work is inspired by the AIR standard from CivitAi [AIR-URN](https://github.com/civitai/civitai/wiki/AIR-%E2%80%90-Uniform-Resource-Names-for-AI) project<br>
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and by the super-resolution registry code from [Spandrel](https://github.com/chaiNNer-org/spandrel/blob/main/libs/spandrel/spandrel/__helpers/registry.py) library.
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## Goals
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- Standard identification scheme for all ML-related development
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- Simplification of code for model-related logistics
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- Rapid retrieval of resources and metadata
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- Efficient and reliable compatability checks
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- Organized hyperparameter management
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