Update README.md

README.md

@@ -1,56 +1,5 @@
----
-title: Nest-AI
-emoji: 🪶
-colorFrom: gray
-colorTo: indigo
-sdk: static
-pinned: false
----
-
 # Nest-AI
 
-Nest-AI is an independent research and experimentation hub focused on model distillation, synthetic dataset design, reasoning-focused training data, and unconventional open-model development.
-
-Our work is built around a simple idea: stronger open models do not come only from scale. They also come from better data, sharper curation, and more deliberate training choices.
-
-## What Nest-AI works on
-
-- Opus-inspired distillation workflows
-- Synthetic reasoning and instruction datasets
-- Experimental fine-tunes for writing, reasoning, and behavior shaping
-- Small and mid-sized open models pushed beyond expected capability
-- Unusual training ideas that explore where data design can outperform brute force
-
-## Why it matters
-
-Nest-AI focuses on practical distillation and dataset craftsmanship aimed at making advanced model behavior more usable in open releases.
-
-A major part of this work has centered on Opus-style data and distill pipelines. That work has become part of many recent Opus-distill conversations and efforts across Hugging Face, especially where builders are trying to preserve strong behavior in smaller, more efficient models.
-
-## Current direction
-
-Nest-AI is especially interested in:
-
-- high-quality synthetic corpora
-- reasoning-heavy supervision
-- creative writing and long-form behavior
-- experimental alignment and response shaping
-- novel training methods that are directionally strong even when they are still early
-
-## Support the work
-
-If you want to support more dataset creation and unique experimental model training:
-
-**Ko-fi:** https://www.ko-fi.com/abcuo
-
-## Business inquiries
-
-For collaborations, partnerships, or business inquiries:
-
-**Website:** https://www.crowfeather.co
-
-## Philosophy
-
-Nest-AI is built around careful experimentation, honest iteration, and the belief that open-model progress can come from original data work as much as from raw compute.
+Nest-AI is an independent research and experimentation hub focused on model distillation, synthetic dataset design, reasoning-focused training data, and unconventional open-model development. Its work centers on pushing small and mid-sized models beyond expected capability through careful curation, structured synthetic corpora, and practical distillation workflows inspired by frontier systems. Nest-AI is especially associated with Opus-style data and experimental training methods aimed at transferring strong behavior into more efficient open releases, with a broader focus on reasoning, creative writing, alignment, and unique fine-tuning strategies.
 
-If you're interested in distillation, synthetic data, reasoning datasets, or unusual training experiments, you're in the right place.
+Nest-AI is built on the idea that stronger open models do not come from scale alone, but also from better data, sharper curation, and more deliberate training choices. Support dataset creation and unique experimental model training at https://www.ko-fi.com/abcuo, and for collaborations or business inquiries visit https://www.crowfeather.co.