README: reorder bottom sections; drop Field/Value header

README.md

@@ -216,6 +216,14 @@ gs://weatherbench2/datasets/hres_t0/2016-2022-6h-240x121_equiangular_with_poles_
 
 Mosaic operates at 1.5° (~166 km), which cannot resolve mesoscale phenomena such as tropical-cyclone inner-core structure or individual severe thunderstorms. The block-sparse attention is designed to scale linearly with sequence length, so finer grids (e.g. 0.25°, ~700k tokens) are a natural next step but are not part of this release.
 
+## Model card metadata
+
+|         |   |
+|---------|---|
+| License | [`cc-by-nc-4.0`](https://creativecommons.org/licenses/by-nc/4.0/) |
+| Library | `pytorch` |
+| Tags    | `weather` · `weather-forecasting` · `climate` · `atmospheric-science` · `sparse-attention` · `transformer` · `probabilistic-forecasting` |
+
 ## License
 
 Released under [CC-BY-NC-4.0](https://creativecommons.org/licenses/by-nc/4.0/). Free for non-commercial research and educational use with attribution; commercial use requires a separate license. Underlying training data (ERA5, HRES) is subject to its own licensing terms set by ECMWF.
@@ -224,14 +232,6 @@ Released under [CC-BY-NC-4.0](https://creativecommons.org/licenses/by-nc/4.0/).
 
 MZ acknowledges support from Microsoft Research AI4Science. JWvdM acknowledges support from the European Union Horizon Framework Programme (Grant agreement ID: 101120237). This work used the Dutch national e-infrastructure with the support of the SURF Cooperative using grant no. EINF-16923. Computations were partially performed using the UvA/FNWI HPC Facility.
 
-## Model card metadata
-
-| Field         | Value |
-|---------------|-------|
-| License       | [`cc-by-nc-4.0`](https://creativecommons.org/licenses/by-nc/4.0/) |
-| Library       | `pytorch` |
-| Tags          | `weather` · `weather-forecasting` · `climate` · `atmospheric-science` · `sparse-attention` · `transformer` · `probabilistic-forecasting` |
-
 ## Citation
 
 If you use Mosaic, please cite: