Update README.md

README.md

@@ -11,18 +11,18 @@ tags:
 library_name: transformers
 ---
 
-# KiteFish-A1-1.5B
+# Minnow-Math-1.5B
 
-**KiteFish-A1-1.5B** is a ~1.5B parameter decoder-only transformer trained from scratch on raw arXiv LaTeX sources across mathematics, computer science, and theoretical physics.
+**Minnow-Math-1.5B** is a ~1.5B parameter decoder-only transformer trained from scratch on raw arXiv LaTeX sources across mathematics, computer science, and theoretical physics.
 
 📄 **Paper:** https://arxiv.org/abs/2602.17288  
-💻 **Github:** https://github.com/kitefishai/KiteFish-A1-1.5B-Math
+💻 **Github:** https://github.com/kitefishai/Minnow-Math-1.5B
 
 This is a **base scientific language model** (not instruction-tuned).
 
 ## Overview
 
-KiteFish-A1-1.5B explores what it takes to train a domain-specialized scientific language model directly from structured LaTeX archives.
+Minnow-Math-1.5B explores what it takes to train a domain-specialized scientific language model directly from structured LaTeX archives.
 
 **Training Scale**
 - ~52B pretraining tokens  
@@ -56,7 +56,7 @@ The focus of this project is *scientific language modeling robustness*, not benc
 
 ## Intended Use
 
-KiteFish-A1-1.5B is suitable for:
+Minnow-Math-1.5B is suitable for:
 
 - Scientific text modeling research  
 - Mathematical language modeling experiments  
@@ -102,7 +102,7 @@ This release is intended primarily for research and experimentation.
 from transformers import AutoTokenizer, AutoModelForCausalLM
 import torch
 
-model_id = "KiteFishAI/KiteFish-A1-1.5B-Math"
+model_id = "KiteFishAI/Minnow-Math-1.5B"
 
 tokenizer = AutoTokenizer.from_pretrained(model_id)
 model = AutoModelForCausalLM.from_pretrained(model_id)