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.DS_Store
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Binary file (12.3 kB). View file
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README.md
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| 1 |
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---
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| 2 |
+
language:
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| 3 |
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- en
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+
library_name: mir
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| 5 |
+
---
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| 6 |
+
<div align="center"><img src="https://github.com/darkshapes/MIR/raw/main/img_src/mir300_dark.png" width="25%"></div>
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| 7 |
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| 8 |
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#
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> [!IMPORTANT]
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| 11 |
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> # MIR (Machine Intelligence Resource)<br><br>A naming schema for AIGC/ML work.
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| 12 |
+
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| 13 |
+
The MIR classification format seeks to standardize and complete a hyperlinked network of model information, improving accessibility and reproducibility across the AI community.<br>
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| 14 |
+
The work is inspired by:
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| 15 |
+
- [AIR-URN](https://github.com/civitai/civitai/wiki/AIR-%E2%80%90-Uniform-Resource-Names-for-AI) project by [CivitAI](https://civitai.com/)
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| 16 |
+
- [Spandrel](https://github.com/chaiNNer-org/spandrel/blob/main/libs/spandrel/spandrel/__helpers/registry.py) library's super-resolution registry
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| 17 |
+
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| 18 |
+
Example:
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| 19 |
+
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| 20 |
+
> [!NOTE]
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> # mir : model . transformer . clip-l : stable-diffusion-xl
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| 23 |
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| 24 |
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```
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| 25 |
+
mir : model . lora . hyper : flux-1
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| 26 |
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↑ ↑ ↑ ↑ ↑
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| 27 |
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[URI]:[Domain].[Architecture].[Series]:[Compatibility]
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| 28 |
+
```
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| 29 |
+
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| 30 |
+
Code for this project can be found at [darkshapes/MIR on GitHub](https://github.com/darkshapes/MIR)
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| 31 |
+
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| 32 |
+
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| 33 |
+
## Definitions:
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| 34 |
+
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| 35 |
+
Like other URI schema, the order of the identifiers roughly indicates their specificity from left (broad) to right (narrow)
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| 36 |
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| 37 |
+
### Domains
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| 38 |
+
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| 39 |
+
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| 40 |
+
- `dev`: Varying local neural network layers, in-training, pre-release, items under evaluation, likely in unexpected formats<br>
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| 41 |
+
- `model`: Static local neural network layers. Publicly released machine learning models with an identifier in the database<br>
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| 42 |
+
- `operations`: Varying global neural network attributes, algorithms, optimizations and procedures on models<br>
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| 43 |
+
- `info`: Static global neural network attributes, metadata with an identifier in the database<br>
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| 44 |
+
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| 45 |
+
### Architecture
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| 46 |
+
Broad and general terms for system architectures.
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| 47 |
+
- `dit`: Diffusion transformer, typically Vision Synthesis
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| 48 |
+
- `unet`: Unet diffusion structure
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| 49 |
+
- `art` : Autoregressive transformer, typically LLMs
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| 50 |
+
- `lora`: Low-Rank Adapter (may work with dit or transformer)
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| 51 |
+
- `vae`: Variational Autoencoder
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| 52 |
+
etc
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| 53 |
+
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| 54 |
+
### Series
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| 55 |
+
Foundational network and technique types.
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| 56 |
+
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| 57 |
+
### Compatibility
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| 58 |
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Implementation details based on version-breaking changes, configuration inconsistencies, or other conflicting indicators that have practical application.
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| 59 |
+
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| 60 |
+
### Goals
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| 61 |
+
- Standard identification scheme for **ALL** fields of ML-related development
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| 62 |
+
- Simplification of code for model-related logistics
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| 63 |
+
- Rapid retrieval of resources and metadata
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| 64 |
+
- Efficient and reliable compatibility checks
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| 65 |
+
- Organized hyperparameter management
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| 66 |
+
|
| 67 |
+
> <details> <summary>Why not use `diffusion`/`sgm`, `ldm`/`text`/hf.co folder-structure/brand or trade name/preprint paper/development house/algorithm</summary>
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| 68 |
+
>
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| 69 |
+
> - The format here isnt finalized, but overlapping resource definitions or complicated categories that are difficult to narrow have been pruned
|
| 70 |
+
> - Likewise, definitions that are too specific have also been trimmed
|
| 71 |
+
> - HF.CO become inconsistent across folders/files and often the metadata enforcement of many important developments is neglected
|
| 72 |
+
> - Development credit often shared, [Paper heredity tree](https://www.connectedpapers.com/search?q=generative%20diffusion), super complicated
|
| 73 |
+
> - Algorithms (esp application) are less common knowledge, vague, ~~and I'm too smooth-brain.~~
|
| 74 |
+
> - Overall an attempt at impartiality and neutrality with regards to brand/territory origins
|
| 75 |
+
> </details>
|
| 76 |
+
|
| 77 |
+
> <details><summary>Why `unet`, `dit`, `lora` over alternatives</summary>
|
| 78 |
+
>
|
| 79 |
+
> - UNET/DiT/Transformer are shared enough to be genre-ish but not too narrowly specific
|
| 80 |
+
> - Very similar technical process on this level
|
| 81 |
+
> - Functional and efficient for random lookups
|
| 82 |
+
> - Short to type
|
| 83 |
+
> </details>
|
| 84 |
+
|
| 85 |
+
> <details><summary>Roadmap</summary>
|
| 86 |
+
>
|
| 87 |
+
> - Decide on `@` or `:` delimiters (like @8cfg for an indistinguishable 8 step lora that requires cfg)
|
| 88 |
+
> - crucial spec element, or an optional, MIR app-determined feature?
|
| 89 |
+
> - Proof of concept generative model registry
|
| 90 |
+
> - Ensure compatability/integration/cross-pollenation with [OECD AI Classifications](https://oecd.ai/en/classification)
|
| 91 |
+
> - Ensure compatability/integration/cross-pollenation with [NIST AI 200-1 NIST Trustworthy and Responsible AI](https://www.nist.gov/publications/ai-use-taxonomy-human-centered-approach)
|
| 92 |
+
> </details>
|
| 93 |
+
|
| 94 |
+
massive thank you to [@silveroxides](https://huggingface.co/silveroxides) for phenomenal work collecting pristine state dicts and related information
|
| 95 |
+
|
| 96 |
+
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hash/.DS_Store
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hash/20250725_b3_layer_0725.json
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| 1 |
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bla{
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| 2 |
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"/Users/unauthorized/Downloads/models/mass_hash/": {
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| 3 |
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"type": "LAYER",
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|
hash/20250725_sha256_layer_0725.json
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hash/20250728_sha226_layer_mlx_20250728171212.json
ADDED
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@@ -0,0 +1,190 @@
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hash/20250728_sha256_file_0725.json
ADDED
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| 1 |
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|
hash/20250728_sha256_file_mlx_20250728171143.json
ADDED
|
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|
| 1 |
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hash/20250731_sha256_('layer_PixArt-XL-2-1024-MS',)_._160438.json
ADDED
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ADDED
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hash/20250731_sha256_file_mass_hash_100926.json
ADDED
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{
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hash/20250731_sha256_layer_kolors-diffusers_blobs_103345.json
ADDED
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