Update README.md

README.md

@@ -13,7 +13,7 @@ base_model:
 
 Tiny Language Model For Japanese and English Bidirectional Translation
 
-- **Purrs on your lap** 🐱: Small and efficient! 0.8-3.3B models that run on edge devices.
+- **Purrs on your lap** 🐱: Small and efficient! 0.8-7B models that run on edge devices.
 - **Swift and Feline Sharp** 🐾: Beats TranslateGemma-12B on text-to-text translation quality.
 - **Adopt and adapt** 🐈: Open source (MIT License) models you can customize and extend.
 
@@ -28,6 +28,7 @@ All models are available on Hugging Face:
 - [CAT-Translate-0.8B](https://huggingface.co/cyberagent/CAT-Translate-0.8b/)
 - [CAT-Translate-1.4B](https://huggingface.co/cyberagent/CAT-Translate-1.4b/)
 - [CAT-Translate-3.3B](https://huggingface.co/cyberagent/CAT-Translate-3.3b/)
+- [CAT-Translate-7B](https://huggingface.co/cyberagent/CAT-Translate-7b/)
 
 ## Evaluation
 
@@ -44,8 +45,7 @@ We conducted evaluation on the translation subsets of the following benchmarks:
 We chose these tasks as benchmarks because (1) they are derived from real world applications and (2) are less overoptimized compared to popular datasets (e.g., WMT).
 
 The results are below.
-Overall, our 1.4B model achieved the best overall scores.
-The 0.8B, 1.4B, and 3.3B-beta models achieved the best scores among all models (including closed source) within their respective sizes for both En-Ja and Ja-En translation tasks.
+All the models achieved the best scores among all models (including closed source) within their respective sizes for both En-Ja and Ja-En translation tasks.