Update README.md

README.md

@@ -78,30 +78,38 @@ You can find the details about evaluation process and the evaluation results.
 Use the code below to get started with the model.
 
 ```python
-import joblib
-import json
+import xgboost as xgb
 import pandas as pd
-clf = joblib.load(MLstructureMining_model.bin)
-with open("config.json") as f:
-    config = json.load(f)
-clf.predict(pd.DataFrame.from_dict(config["sklearn"]["example_input"]))
+
+N_CPU = 8  # Number of CPUs used
+
+# Load model
+bst = xgb.Booster({'nthread': N_CPU})
+bst.load_model("MLstructureMining_model.bin")
+
+# Load your data
+# data = pd.read_csv("your_data.csv")
+# data_xgb = xgb.DMatrix(data)
+
+# Do inference
+pred = bst.predict(data_xgb)
 ```
 
 
 # Model Card Authors
 
 This model card is written by following authors:
-
-[More Information Needed]
+Emil T. S. Kjær
 
 # Model Card Contact
 
 You can contact the model card authors through following channels:
-[More Information Needed]
+emil.thyge.kjær@gmail.com
 
 # Citation
 
 Below you can find information related to citation.
+In review.
 
 **BibTeX:**
 ```