chore: update model

README.md

@@ -1,8 +1,7 @@
 
 # Model description
 
-
-    The locus-to-gene (L2G) model derives features to prioritise likely causal genes at each GWAS locus based on genetic and functional genomics features. The main categories of predictive features are:
+The locus-to-gene (L2G) model derives features to prioritise likely causal genes at each GWAS locus based on genetic and functional genomics features. The main categories of predictive features are:
     - Distance: (from credible set variants to gene)
     - Molecular QTL Colocalization
     - Chromatin Interaction: (e.g., promoter-capture Hi-C)
@@ -51,8 +50,7 @@
 
 # How to Get Started with the Model
 
-
-    To use the model, you can load it using the `LocusToGeneModel.load_from_hub` method. This will return a `LocusToGeneModel` object that can be used to make predictions on a feature matrix.
+To use the model, you can load it using the `LocusToGeneModel.load_from_hub` method. This will return a `LocusToGeneModel` object that can be used to make predictions on a feature matrix.
     The model can then be used to make predictions using the `predict` method.
     More information at: https://opentargets.github.io/gentropy/python_api/methods/l2g/model/
     

l2g_model_1006.pkl

@@ -1,3 +1,3 @@
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