Update README.md

README.md

@@ -18,7 +18,7 @@ tags:
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/64e174e202fa032de4143324/CfIE4_oZgpNsNZyurjO7D.png)
 I’m excited to introduce my third-generation model:
 # Qwen2.5-14B-1M-YOYO-V3
-This time, I’m not only releasing the model but also sharing some model merging techniques, which might be even more valuable than the model itself.
+This time, I not only released the model but also shared some model merging insights that might be even more valuable than the model itself.
 
 Let’s start by looking at the initial merge configuration (YAML):
 ```yaml
@@ -29,9 +29,9 @@ models:
   - model: Qwen/Qwen2.5-14B-instruct-1M  
 dtype: bfloat16
 ```
-Seems straightforward, right? But the merged model occasionally suffered from **uncontrollable outputs**, likely due to the large divergence between the instruction-tuned models and the base model.
+Does this seem flawless? However, merged models occasionally exhibit **uncontrollable outputs**, likely due to significant discrepancies between instruction-tuned models and base models.
 
-To address this, I first tried integrating a fine-tuned model with smaller divergence from the base model, like **Virtuoso-Small-v2**.
+To address this, I first attempted to directly integrate a fine-tuned model with smaller divergence from the base model, such as **Virtuoso-Small-v2**.
 
 This gave rise to [Qwen2.5-14B-YOYO-latest-V2](https://huggingface.co/YOYO-AI/Qwen2.5-14B-YOYO-latest-V2).
 ```yaml
@@ -192,4 +192,4 @@ int8_mask: true
 normalize: true  
 name: Qwen2.5-14B-1M-YOYO-V3
 ```
-Feel free to adapt these strategies for your own merging experiments! 🚀
+I hope this helps!