Update README.md

README.md

@@ -3,7 +3,7 @@ language:
 - en
 library_name: mir
 ---
-<div align="center"><img src="https://github.com/darkshapes/MIR/raw/main/img_src/mir300_dark.png" width="25%"></div>
+<div align="center"><img src="https://github.com/darkshapes/entity-statement/raw/main/png/mir/mir300_dark.png" width="25%"></div>
 
 
 #
@@ -18,18 +18,79 @@ The work is inspired by:
 Example:
 
 > [!NOTE]
-> # mir :// model.vit.clip-vit-l-patch14:stable-diffusion-xl-1
+> # mir : model . transformer . clip-l : stable-diffusion-xl
 
 
 ```
  mir : model .    lora      .    hyper    :   flux-1
   ↑      ↑         ↑               ↑            ↑
- [URI]://[Domain].[Architecture].[Series]:[Compatibility]
+ [URI]:[Domain].[Architecture].[Series]:[Compatibility]
 ```
 
-This dataset is a cache of hash values and layer names extracted from various models and saved to `json` files. Their purpose is for cataloging model architectures across a broad diversity of applications, and for building a comprehensive recognition network using MIR identifiers for [nnll](https://github.com/darkshapes/nnll). Code for this project can be found at [MIR](https://github.com/darkshapes/MIR) and [nnll](https://github.com/darkshapes/nnll) project pages.
+Code for this project can be found at [darkshapes/MIR on GitHub](https://github.com/darkshapes/MIR)
 
-More information about MIR available at [darkshapes wiki](https://github.com/darkshapes/sdbx/wiki/_MIR:-Usage)
 
+## Definitions:
+
+Like other URI schema, the order of the identifiers roughly indicates their specificity from left (broad) to right (narrow)
+
+### Domains
+
+
+- `dev`: Varying local neural network layers, in-training, pre-release, items under evaluation, likely in unexpected formats<br>
+- `model`: Static local neural network layers. Publicly released machine learning models with an identifier in the database<br>
+- `operations`: Varying global neural network attributes, algorithms, optimizations and procedures on models<br>
+- `info`:  Static global neural network attributes, metadata with an identifier in the database<br>
+
+### Architecture
+Broad and general terms for system architectures.
+- `dit`: Diffusion transformer, typically Vision Synthesis
+- `unet`: Unet diffusion structure
+- `art` : Autoregressive transformer, typically LLMs
+- `lora`: Low-Rank Adapter (may work with dit or transformer)
+- `vae`: Variational Autoencoder
+etc
+
+### Series
+Foundational network and technique types.
+
+### Compatibility
+Implementation details based on version-breaking changes, configuration inconsistencies, or other conflicting indicators that have practical application.
+
+### Goals
+- Standard identification scheme for **ALL** fields of ML-related development
+- Simplification of code for model-related logistics
+- Rapid retrieval of resources and metadata
+- Efficient and reliable compatibility checks
+- Organized hyperparameter management
+
+> <details> <summary>Why not use `diffusion`/`sgm`, `ldm`/`text`/hf.co folder-structure/brand or trade name/preprint paper/development house/algorithm</summary>
+>
+> - The format here isnt finalized, but overlapping resource definitions or complicated categories that are difficult to narrow have been pruned
+> - Likewise, definitions that are too specific have also been trimmed
+> - HF.CO become inconsistent across folders/files and often the metadata enforcement of many important developments is neglected
+> - Development credit often shared, [Paper heredity tree](https://www.connectedpapers.com/search?q=generative%20diffusion), super complicated
+> - Algorithms (esp application) are less common knowledge, vague, ~~and I'm too smooth-brain.~~
+> - Overall an attempt at impartiality and neutrality with regards to brand/territory origins
+> </details>
+
+> <details><summary>Why `unet`, `dit`, `lora` over alternatives</summary>
+>
+> - UNET/DiT/Transformer are shared enough to be genre-ish but not too narrowly specific
+> - Very similar technical process on this level
+> - Functional and efficient for random lookups
+> - Short to type
+> </details>
+
+> <details><summary>Roadmap</summary>
+>
+> - Decide on `@` or `:` delimiters (like @8cfg for an indistinguishable 8 step lora that requires cfg)
+> - crucial spec element, or an optional, MIR app-determined feature?
+> - Proof of concept generative model registry
+> - Ensure compatability/integration/cross-pollenation with [OECD AI Classifications](https://oecd.ai/en/classification)
+> - 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)
+> </details>
+
+massive thank you to [@silveroxides](https://huggingface.co/silveroxides) for phenomenal work collecting pristine state dicts and related information
 
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/65ff1816871b36bf84fc3c37/NWZideVk_pp_4OzQDl96w.png)