pickled model

config.json

@@ -2,7 +2,7 @@
     "sklearn": {
         "columns": ["fixed_acidity", "volatile_acidity", "citric_acid", "residual_sugar", "chlorides", "free_sulfur_dioxide", "total_sulfur_dioxide", "density", "pH", "sulphates", "alcohol"],
         "environment": [
-            "scikit-learn=0.24.2"
+            "scikit-learn=1.2.2"
         ],
         "example_input": {
           "fixed_acidity": ["7.4", "7.8", "10.3"],
@@ -18,7 +18,7 @@
           "alcohol": ["9.4", "9.8", "12.6"]
         },
         "model": {
-            "file": "sklearn_model.joblib"
+            "file": "model.pkl"
         },
         "task": "tabular-classification"
     }

convert.py

@@ -0,0 +1,12 @@
+from typing import Dict, List, Union
+import os
+import joblib
+import numpy as np
+
+features = ["fixed_acidity", "volatile_acidity", "citric_acid", "residual_sugar", "chlorides", "free_sulfur_dioxide", "total_sulfur_dioxide", "density", "pH", "sulphates", "alcohol"]
+
+model = joblib.load("sklearn_model.joblib")
+model_path = "model.pkl"
+
+with open(model_path, mode="bw") as f:
+    pickle.dump(model, file=f)

pipeline.py

@@ -3,6 +3,7 @@ import os
 import joblib
 import numpy as np
 
+
 features = ["fixed_acidity", "volatile_acidity", "citric_acid", "residual_sugar", "chlorides", "free_sulfur_dioxide", "total_sulfur_dioxide", "density", "pH", "sulphates", "alcohol"]
 
 class PreTrainedPipeline():

requirements.txt

@@ -1,3 +1,3 @@
+scikit-learn=1.2.2
 joblib==1.2.0
-scikit-learn==0.24.2
 numpy==1.24.3