Update README.md

README.md

@@ -29,7 +29,7 @@ The resulting model is the **InfiR2-7B-Instruct-FP8**.
 
 **Training Recipe**:
 <p align="center">
-    <img src="fp8_recipe.png" width="100%"/>
+    <img src="fp8_recipe.png" width="80%"/>
 <p>
 
 - Stable and Reproducible Performance
@@ -47,7 +47,7 @@ The InfiR2 framework offers multiple variants model with different size and trai
 - **7B**
 - [InfiR2-7B-base-FP8](https://huggingface.co/InfiX-ai/InfiR2-7B-base-FP8): *Continue pretrain on Qwen2.5-7B-base*
 - [InfiR2-7B-Instruct-FP8](https://huggingface.co/InfiX-ai/InfiR2-7B-Instruct-FP8): *Supervised fine-tuning on InfiR2-7B-base-FP8 with [InfiAlign dataset](https://huggingface.co/papers/2508.05496)*
-- [InfiR2-R1-7B-FP8](https://huggingface.co/InfiX-ai/InfiR2-R1-7B-FP8): *Reinforcement learning on InfiR2-7B-Instruct-FP8 with dapo dataset*
+- [InfiR2-R1-7B-FP8-Preview](https://huggingface.co/InfiX-ai/InfiR2-R1-7B-FP8-Preview): *Multi-stage FP8 Reinforcement Learning*
 
 ## 📊 Model Performance
 Below is the performance comparison of InfiR2-7B-Instruct-FP8 on reasoning benchmarks. Note: 'w. InfiAlign' denotes Supervised Fine-Tuning (SFT) using the InfiAlign dataset.