Update README.md

README.md

@@ -52,12 +52,11 @@ datasets:
 - MORPH-FM-Ti: ~7M with 4 levels of finetuning including LoRA.
 - MORPH-FM-S: ~30M with 4 levels of finetuning including LoRA.
 - MORPH-FM-M: ~120M with 4 levels of finetuning including LoRA.
-- MORPH-FM-L: ~500M with 4 levels of finetuning including LoRA.
-- MORPH-FM-XL: **~1.2B (coming up soon)**.
+- MORPH-FM-L: ~500M with 4 levels of finetuning including LoRA (we prefer LoRA).
+- MORPH-FM-XL: 1.2B with 4 levels of finetuning including LoRA (we prefer LoRA).
 - MORPH-SS-Ti: ~7M standalone models for 13 datasets.
 - MORPH-SS-S: ~30M standalone models for 13 datasets.
 
-
 ## Architecture:
 - MORPH is built on a convolutional vision transformer backbone that seamlessly handles heterogeneous spatiotemporal
 datasets of varying data dimensionality (1D–3D) at different resolutions, multiple