Add robotics pipeline tag and improve model card

README.md

@@ -1,12 +1,17 @@
 ---
 license: cc-by-4.0
+pipeline_tag: robotics
+tags:
+- visual-navigation
+- sim-to-real
+- topological-navigation
 ---
 
 # FAINT
 
 Fast, Appearance-Invariant Navigation Transformer (FAINT) is a learned policy for vision-based topological navigation.
 
-Please see the [Project Page](https://lasuomela.github.io/faint/) for more information.
+[**Paper**](https://huggingface.co/papers/2509.11791) | [**Project Page**](https://lasuomela.github.io/faint/) | [**GitHub**](https://github.com/lasuomela/FAINT)
 
 ## Model Details
 
@@ -18,13 +23,13 @@ This repo contains two versions of the trained model weights.
 
 ## Usage
 
-See the main Github [repo](https://github.com/lasuomela/FAINT) for details, input preprocessing etc.
+See the main GitHub [repo](https://github.com/lasuomela/FAINT) for details regarding input preprocessing, deployment with ROS2, and training.
 
 ### Torchscript
 
 Only dependency is Pytorch.
 
-```bash
+```python
 import torch
 ckpt_path = 'FAINT-Real/model_torchscript.pt'
 model = torch.jit.load(ckpt_path)
@@ -32,9 +37,9 @@ model = torch.jit.load(ckpt_path)
 
 ### Pytorch
 
-Need to have the Faint library installed.
+Need to have the FAINT library installed.
 
-```bash
+```python
 import torch
 from faint.common.models.faint import FAINT
 
@@ -51,7 +56,7 @@ If you use FAINT in your research, please use the following BibTeX entry:
 ```bibtex
 @article{suomela2025synthetic,
   title={Synthetic vs. Real Training Data for Visual Navigation},
-  author={Suomela, Lauri and Kuruppu Arachchige, Sasanka and Torres, German F. and Edelman, Harry and Kämäräinen, Joni-Kristian}
+  author={Suomela, Lauri and Kuruppu Arachchige, Sasanka and Torres, German F. and Edelman, Harry and Kämäräinen, Joni-Kristian},
   journal={arXiv:2509.11791},
   year={2025}
 }