Update README.md

README.md

@@ -19,7 +19,7 @@ This model is a fine-tuned and quantized version of the **NuExtract 8B** paramet
 
 ## Model Description
 
-This model is a working proof of concept for a meaningful hypothesis: that the semantically rich, human-stewarded data maintained by 211 networks is not limited by its lack of machine-readable structure. With targeted fine-tuning, AI can bridge that gap — preserving the accuracy and nuance of human curation while producing the structured outputs that governments, hospitals, researchers, and software providers need to build effective solutions around the social safety net.
+This model is a working proof of concept for a meaningful hypothesis: that the semantically rich, human-stewarded data maintained by some 211 networks (especially in rural areas) is not limited by its lack of machine-readable structure. With targeted fine-tuning, AI can bridge that gap — preserving the accuracy and nuance of human curation while producing the structured outputs that governments, hospitals, researchers, and software providers need to build effective solutions around the social safety net.
 
 This model was trained as a follow-up to our initial experiments with the Osmosis 0.6B model. While the 0.6B model successfully learned the schema fields and could handle basic cases, it struggled with the complex realities of RFC 5545 RRULE schedule data. To overcome this limitation and ensure high-quality, strict structural adherence, we fine-tuned the highly capable **NuExtract 8B** model.