add eval to docs

docs/nerfology/methods/splat.md

@@ -31,6 +31,16 @@ Because the method trains on *full images* instead of bundles of rays, there is
 ### Running the Method
 To run splatfacto, run `ns-train splatfacto --data <data>`. Just like NeRF methods, the splat can be interactively viewed in the web-viewer, loaded from a checkpoint, rendered, and exported.
 
+We provide a few additional variants:
+
+| Method           | Description                    | Memory | Speed   |
+| ---------------- | ------------------------------ | ------ | ------- |
+| `splatfacto`     | Default Model                  | ~6GB   | Fast    |
+| `splatfacto-big` | Larger higher quality          | ~12GB  | Slower  |
+
+
+A full evalaution of Nerfstudio's implementation of Gaussian Splatting against the original Inria method can be found [here](https://docs.gsplat.studio/tests/eval.html).
+
 #### Quality and Regularization
 The default settings provided maintain a balance between speed, quality, and splat file size, but if you care more about quality than training speed or size, you can decrease the alpha cull threshold 
 (threshold to delete translucent gaussians) and disable culling after 15k steps like so: `ns-train splatfacto --pipeline.model.cull_alpha_thresh=0.005 --pipeline.model.continue_cull_post_densification=False --data <data>`