Update model card metadata and add sample usage

README.md

@@ -1,5 +1,4 @@
 ---
-license: mit
 datasets:
 - Zatom-AI/qm9
 - Zatom-AI/mp_20
@@ -10,7 +9,8 @@ datasets:
 - Zatom-AI/mptrj
 language:
 - en
-pipeline_tag: graph-ml
+license: mit
+pipeline_tag: other
 tags:
 - chemistry
 - biology
@@ -37,12 +37,42 @@ tags:
 
 </div>
 
-This repository contains the model weights for Zatom-1, as introduced in [Zatom-1: A Multimodal Flow Foundation Model for 3D Molecules and Materials](https://huggingface.co/papers/2602.22251).
+This repository contains the model weights for **Zatom-1**, the first end-to-end foundation model that unifies generative and predictive learning of 3D molecules and materials. Introduced in [Zatom-1: A Multimodal Flow Foundation Model for 3D Molecules and Materials](https://huggingface.co/papers/2602.22251), Zatom-1 is a Transformer trained with a multimodal flow matching objective that jointly models discrete atom types and continuous 3D geometries.
 
 ## GitHub repository
 
+For the full implementation, training scripts, and configuration files, visit:
 https://github.com/Zatom-AI/zatom
 
+## Sample Usage
+
+### Installation
+
+To get started, clone the repository and install the dependencies:
+
+```bash
+# Clone project
+git clone https://github.com/Zatom-AI/zatom
+cd zatom
+
+# Install requirements
+pip install -e '.[cuda]'
+```
+
+### Evaluation
+
+To generate evaluation metrics for molecule and material generation using the Zatom-1 weights:
+
+```bash
+python zatom/eval_fm.py \
+    ckpt_path=checkpoints/zatom_1_joint_paper_weights.ckpt \
+    model.sampling.num_samples=10000 \
+    model.sampling.batch_size=1000 \
+    name=eval_run \
+    seed=42 \
+    trainer=gpu
+```
+
 ## Open-source resources
 
 Zatom-1 builds upon the source code and data from the following projects: