fixes 3

Author: isaacmg

README.md

@@ -42,6 +42,7 @@ Using the library
 
 We have a number of models we are planning on releasing soon. [Please check our project board for more info](https://github.com/AIStream-Peelout/flow-forecast/projects/5)
 
+
 **Integrations**
 
 [Google Cloud Platform](https://github.com/AIStream-Peelout/flow-forecast/wiki/Cloud-Provider-Integration)

flood_forecast/pytorch_training.py

@@ -105,7 +105,7 @@ def train_transformer_style(
     :type takes_target: bool, optional
     :param forward_params: [description], defaults to {}
     :type forward_params: Dict, optional
-    :param model_filepath: The file path to load modeel weights from, defaults to "model_save"
+    :param model_filepath: The file path to load model weights from, defaults to "model_save"
     :type model_filepath: str, optional
     """
     use_wandb = model.wandb

flood_forecast/trainer.py

@@ -222,5 +222,6 @@ def main():
     train_function(training_config["model_type"], training_config)
     print("Process is now complete.")
 
+
 if __name__ == "__main__":
     main()

flood_forecast/transformer_xl/data_embedding.py

@@ -151,7 +151,7 @@ def forward(self, x):
 
 
 class TemporalEmbedding(nn.Module):
-    def __init__(self, d_model, embed_type='fixed', lowest_level=4):
+    def __init__(self, d_model: int, embed_type='fixed', lowest_level=4):
         """A class to create.
 
         :param d_model: The model embedding dimension