Update README.md

README.md

@@ -9,10 +9,10 @@ license: mit
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 ## **Training & Fine-Tuning**
-RombUltima-32B is based on a **linear merge** of its parent models using equal weighting (0.5 each), resulting in a **balanced fusion** that leverages both structured knowledge from Rombos and enhanced generalization from Ultima.
+RombUltima-32B is based on a **slerp merge** of its parent models using equal weighting (0.5 each), resulting in a **balanced fusion** that leverages both structured knowledge from Rombos and enhanced generalization from Ultima.
 
 - **Tokenization Approach:** Uses a **union-based tokenizer** to maximize vocabulary coverage.
-- **Precision:** Trained and fine-tuned in **float16** for efficient inference.
+- **Precision:** Trained and fine-tuned in **bfloat16** for efficient inference.
 - **Long-Context Support:** Supports up to **32K tokens** (based on Qwen-32B), with stable generation up to **8K tokens**, depending on hardware constraints.
 - **Multilingual Strength:** Strong performance in **English, French, Chinese, and other global languages**.