Add model card README

README.md

@@ -5,26 +5,7 @@ license_link: >-
   https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-agreement/
 ---
 
-# PhysicsNeMo Checkpoints: FIGConvNet DrivAerML Surface
-
-## Basic Information
-
-- Name: `figconvnet_drivaerml_surface`
-- Publisher: `NVIDIA`
-- Display Name: `PhysicsNeMo Checkpoints: FIGConvNet DrivAerML Surface`
-- Precision: `FP32`
-- Model Format: `PyTorch PTH`
-- Description:
-
-    ```text
-    FIGConvNet DrivAerML Surface is a deep learning model for predicting surface
-    aerodynamic fields on automotive geometries from DrivAerML dataset.
-    The model predicts pressure and wall shear stress fields.
-    ```
-
-- Logo: `https://www.nvidia.com/content/dam/en-zz/Solutions/about-nvidia/logo-and-brand/01-nvidia-logo-vert-500x200-2c50-p@2x.png`
-
-## Description:
+# FIGConvNet DrivAerML Surface
 
 FIGConvNet DrivAerML Surface is a deep learning model for predicting surface
 aerodynamic fields on automotive geometries. The model predicts pressure and
@@ -33,22 +14,22 @@ dynamics (CFD) applications.
 
 This model is available for commercial use.
 
-## License/Terms of Use:
+### License/Terms of Use:
 
 GOVERNING TERMS: The model is governed by the [NVIDIA Software License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-software-license-agreement/)
 and [Product-Specific Terms for AI Products](https://www.nvidia.com/en-us/agreements/enterprise-software/product-specific-terms-for-ai-products/);
 and the use of this model is governed by the [NVIDIA Community Model License](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-community-models-license/).
 
-## Deployment Geography:
+### Deployment Geography:
 
 Global
 
-## Use Case:
+### Use Case:
 
 Computational Fluid Dynamics (CFD) engineers accelerating
 automotive external aerodynamics with AI.
 
-## Release Date:
+### Release Date:
 
 
 ## Reference(s):
@@ -126,7 +107,7 @@ training and inference times compared to CPU-only solutions.
 
 **Model Version:** 1.0.0
 
-## Training, Testing, and Evaluation Datasets:
+# Training, Testing, and Evaluation Datasets:
 
 The DrivAerML dataset is used for training and evaluation, which is a publicly available,
 high-fidelity dataset comprising aerodynamic data for 500 parametrically morphed variants