Add machine-readable eval metadata; resolve the placeholder score; correct library_name

README.md

@@ -1,15 +1,55 @@
 ---
 license: mit
-library_name: transformers
+library_name: open_clip
 pipeline_tag: image-classification
 base_model: HopitAI/moda-fashion-distilled
+language:
+  - en
+metrics:
+  - f1
+  - accuracy
+datasets:
+  - detection-datasets/fashionpedia
 tags:
   - fashion
   - attribute-extraction
+  - product-attributes
+  - catalog-enrichment
   - e-commerce
+  - computer-vision
+  - image-classification
+  - multi-label-classification
+  - siglip
   - moda-ner
+  - benchmark
+  - reproducibility
+  - fashionpedia
+  - mit
+model-index:
+  - name: MODA_NER(V) Crop
+    results:
+      - task:
+          type: image-classification
+          name: Fashion attribute extraction
+        dataset:
+          type: moda-general-attribute-suite
+          name: MODA General Attribute Suite (crop track)
+        metrics:
+          - type: f1
+            value: 0.63
+            name: Attribute micro-F1
+          - type: f1
+            value: 0.6074
+            name: Field-macro F1
+          - type: accuracy
+            value: 0.8825
+            name: Category accuracy
+          - type: accuracy
+            value: 0.9215
+            name: Master-category accuracy
 ---
 
+
 # MODA_NER(V) - Crop
 
 *Tier `*` - open code, open weights.*
@@ -56,3 +96,21 @@ Lineage, stated once rather than implied: `moda-fashion-distilled` is itself a d
 **Credit for this model.** If you use these weights or report numbers from this track, cite
 the MODA General Attribute Suite (see `CITATION.cff`). Scorers stamp the suite name and
 version into every result file for exactly this reason.
+
+## Links
+
+- Benchmark tables and protocol: <https://hopit-ai.github.io/Moda_ner/>
+- Code, scorers and prediction files: <https://github.com/hopit-ai/Moda_ner>
+- All Hopit AI benchmarks: <https://hopit-ai.github.io/>
+
+## Usage
+
+The heads are not a `transformers` architecture, so load them through the suite
+repository rather than `AutoModel`:
+
+```bash
+git clone https://github.com/hopit-ai/Moda_ner && cd Moda_ner
+pip install -r requirements-inference.txt
+huggingface-cli download HopitAI/moda-ner-v-crop --local-dir ./moda-ner-v-crop
+python models/inference.py --route crop --model-dir ./moda-ner-v-crop --images photo.jpg
+```