Update README.md

README.md

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-license: cdla-permissive-2.0
+license: apache-2.0
+title: README
+emoji: 📈
+colorFrom: red
+colorTo: blue
+sdk: static
+pinned: false
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 Prithvi WxC is a 2.3 billion parameter model trained on 160 different variables from MERRA-2 data. It has been pretrained on both forecasting and masked
 reconstruction objectives. I.e.~the model is capable of reconstructing atmospheric state from partial information as well as propagating state into the
 future. The model takes data from two timestamps as input and generates a single, possibly future, timestamp as output. Currently Prithvi WxC comes in two flavors:
 
-- (This model)`prithvi.wxc.rollout.2300m.v1` has been through further training cycles to be optimzed for autoregressive rollout. Here, we restricted the input delta
+- `prithvi.wxc.2300m.v1` has been pretrained with a 50% masking ratio. The time delta between input timestamps is variable as is the forecast lead time.
+  During pretraining, the input delta was chosen from [-3, -6, -9, -12] hours while the forecast lead time was chosen from [0, 6, 12, 24] hours. We recommend using
+  `prithvi.wxc.2300m.v1` for generic use cases that do not focus on forecasting.
+- (This model) `prithvi.wxc.rollout.2300m.v1` has been through further training cycles to be optimzed for autoregressive rollout. Here, we restricted the input delta
   as well as the lead time to 6 hours. We recommend using `prithvi.wxc.rollout.2300m.v1` for forecasting applications.
 
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