Update README.md

README.md

@@ -1,3 +1,9 @@
+---
+license: apache-2.0
+language:
+- en
+library_name: transformers
+---
 # AnalysisObjectTransformer Model
 
 This repository contains the implementation of the AnalysisObjectTransformer model, a deep learning architecture designed for event classification with reconstructed-object inputs. MultiHeadAttention is used to extract the correlation between jets (hadrons) in the final state. Achieves state-of-the-art performance on final states which can be summarized as jets accompanied by missing transverse energy.
@@ -15,7 +21,19 @@ The AnalysisObjectTransformer model is structured to process jet-level features
 
 ## Usage
 
+Firstly, clone the repository: 
+```bash
+git clone https://huggingface.co/maciek-g/AnalysisObjectTransformer
+```
+You can then import the model object and use within standard PyTorch and PyTorch lightning training workflows.
+
 ```python
 from particle_transformer import AnalysisObjectTransformer
 
 model = AnalysisObjectTransformer(input_dim_obj=..., input_dim_event=..., embed_dims=..., linear_dims1=..., linear_dims2=..., mlp_hidden_1=..., mlp_hidden_2=..., num_heads=...)
+```
+
+## Parameter definitions
+
+`input_dim_obj`: The number of features associated with each event object (features per jet, lepton etc..)
+`input_dim_events`: The number of features associated with the event (Number of jets, total hadronic energy, total missing transverse energy etc..)