Update README.md

README.md

@@ -8,7 +8,7 @@ pipeline_tag: text-generation
 library_name: transformers
 ---
 
-# Jan-edge: Distilled for Edge, Built for Agents
+# Jan-v1-edge: Distilled for Edge, Built for Agents
 
 [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue?logo=github)](https://github.com/menloresearch/deep-research)
 [![License](https://img.shields.io/badge/License-Apache%202.0-yellow)](https://opensource.org/licenses/Apache-2.0)
@@ -16,29 +16,29 @@ library_name: transformers
 
 ## Overview
 
-**Jan-edge** is a lightweight agentic model built for fast, reliable on-device execution. As the second release in the **Jan Family**, it is distilled from the larger [`Jan-v1`](https://huggingface.co/janhq/Jan-v1-4B) model, preserving strong reasoning and problem-solving ability in a smaller footprint suitable for resource-constrained environments.
+**Jan-v1-edge** is a lightweight agentic model built for fast, reliable on-device execution. As the second release in the **Jan Family**, it is distilled from the larger [`Jan-v1`](https://huggingface.co/janhq/Jan-v1-4B) model, preserving strong reasoning and problem-solving ability in a smaller footprint suitable for resource-constrained environments.
 
-Jan-edge was developed through a two-phase post-training process. The first phase, **Supervised Fine-Tuning (SFT)**, transferred core capabilities from the `Jan-v1` teacher model to the smaller student. The second phase, **Reinforcement Learning with Verifiable Rewards (RLVR)** —the same method used in `Jan-v1` and `Lucy`—further optimized reasoning efficiency, tool use, and correctness. This staged approach delivers reliable results on complex, interactive workloads.
+Jan-v1-edge was developed through a two-phase post-training process. The first phase, **Supervised Fine-Tuning (SFT)**, transferred core capabilities from the `Jan-v1` teacher model to the smaller student. The second phase, **Reinforcement Learning with Verifiable Rewards (RLVR)** —the same method used in `Jan-v1` and `Lucy`—further optimized reasoning efficiency, tool use, and correctness. This staged approach delivers reliable results on complex, interactive workloads.
 
 ## Performance
 
 ### Question Answering(SimpleQA)
 
-Despite having only 1.7B parameters, **Jan-edge** achieves 83% accuracy—nearly matching the larger Jan-nano-128k—demonstrating its efficiency and robustness.
+Despite having only 1.7B parameters, **Jan-v1-edge** achieves 83% accuracy—nearly matching the larger Jan-nano-128k—demonstrating its efficiency and robustness.
 
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/655e3b59d5c0d3db5359ca3c/ZZvc-vZrC8Wap4zGx5kfL.png)
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/655e3b59d5c0d3db5359ca3c/gV6Ph1m3rW6KeYkpj_b4s.png)
 
 ### Chat & Instruction Following
 
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/655e3b59d5c0d3db5359ca3c/4yQHrbyJ_poeXpyyogKuu.png)
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/655e3b59d5c0d3db5359ca3c/xNWL41L__oULHJkuAaGGt.png)
 
-Versus Qwen 3 1.7B Thinking, Jan-edge shows a slight degradation on instruction-following and CreativeWriting, while remaining comparable or better on EQBench and recency QA.
+Versus Qwen 3 1.7B Thinking, Jan-v1-edge shows a slight degradation on instruction-following and CreativeWriting, while remaining comparable or better on EQBench and recency QA.
 
 ## Quick Start
 
 ### Integration with Jan App
 
-Jan-v1 is optimized for direct integration with the [Jan App](https://jan.ai/). Simply select the model from the Jan App interface for immediate access to its full capabilities.
+Jan-v1-edge is optimized for direct integration with the [Jan App](https://jan.ai/). Simply select the model from the Jan App interface for immediate access to its full capabilities.
 
 ### Local Deployment
 
@@ -72,7 +72,7 @@ max_tokens: 2048
 
 ## 🤝 Community & Support
 
--   **Discussions**: [HuggingFace Community](https://huggingface.co/janhq/Jan-edge/discussions)
+-   **Discussions**: [HuggingFace Community](https://huggingface.co/janhq/Jan-v1-edge/discussions)
 -   **Jan App**: Discover more about the Jan App at [jan.ai](https://jan.ai/)
 
 ## 📄 Citation