Card: say what D1A is first, with an example

README.md

@@ -11,8 +11,14 @@ pipeline_tag: text-classification
 ---
 # D1A-E4B v0.6 · Core ML (text, ≤ 512 tokens)
 
-D1A-E4B v0.6 for the Apple Neural Engine. D1A is a small decision model: a document and typed questions go in, and a
-calibrated probability for every option comes out, in one pass, with no generated text ([jonpol01/d1a](https://github.com/jonpol01/d1a)).
+**A small decision model for the Apple Neural Engine: give it a document and a few questions, and it picks the answers.** Each question
+is yes/no, multiple choice or a score; D1A returns a calibrated probability for every option in one forward pass, with no
+generated text, so every answer is a valid option.
+
+This is the Core ML build: text only, documents up to 512 tokens, about 1.8 s per request on an M4's Neural Engine, 6.1 GB.
+For photos, voice, video, longer documents or more speed (0.63 s on the M4's GPU), use the MLX build
+[JohnP1/d1a-e4b-mlx-q8](https://huggingface.co/JohnP1/d1a-e4b-mlx-q8). D1A labels pull requests, routes requests and triages
+messages; it is built on Google's Gemma 4 E4B ([jonpol01/d1a](https://github.com/jonpol01/d1a)).
 This repository is the text model converted to Core ML; the conversion is described in jonpol01/d1a#224.
 
 ## Status