Update README.md

README.md

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 <!-- Provide a quick summary of what the model is/does. -->
 
-Nora is an open vision-language-action model trained on  robot manipulation episodes from the Open X-Embodiment dataset. The model takes language instructions and camera images as input and generates robot actions. Nora is trained directly from Qwen 2.5 VL-3B.
-All Nora checkpoints, as well as our training codebase are released under an MIT License.
+Nora is an open vision-language-action model trained on robot manipulation episodes from the [Open X-Embodiment](https://robotics-transformer-x.github.io/) dataset. The model takes language instructions and camera images as input and generates robot actions. Nora is trained directly from Qwen 2.5 VL-3B.
+All Nora checkpoints, as well as our [training codebase](https://github.com/declare-lab/nora) are released under an MIT License.
 
 
 
@@ -24,15 +24,18 @@ All Nora checkpoints, as well as our training codebase are released under an MIT
 - **License:** MIT
 - **Finetuned from model :** Qwen 2.5 VL-3B
 
-### Model Sources [optional]
+### Model Sources 
 
 <!-- Provide the basic links for the model. -->
 
 - **Repository:** https://github.com/declare-lab/nora
-- **Paper [optional]:** https://www.arxiv.org/abs/2504.19854
-- **Demo [optional]:** https://declare-lab.github.io/nora
+- **Paper :** https://www.arxiv.org/abs/2504.19854
+- **Demo:** https://declare-lab.github.io/nora
 
+## Usage
 
+Nora take a language instruction and a camera image of a robot workspace as input, and predict (normalized) robot actions consisting of 7-DoF end-effector deltas of the form (x, y, z, roll, pitch, yaw, gripper). 
+To execute on an actual robot platform, actions need to be un-normalized subject to statistics computed on a per-robot, per-dataset basis.