Upload folder using huggingface_hub

Dockerfile

@@ -1,3 +1,4 @@
+
 FROM python:3.9-slim
 WORKDIR /app
 

app.py

@@ -1,9 +1,10 @@
+
 from flask import Flask, request, jsonify
 import joblib
 import pandas as pd
 
 # Load trained model
-model = joblib.load("best_model.pkl")
+model = joblib.load("deployment_files/best_model.pkl")
 
 app = Flask(__name__)
 
@@ -23,3 +24,4 @@ def predict():
 
 if __name__ == "__main__":
     app.run(host="0.0.0.0", port=7860)  # Hugging Face expects 7860
+

best_model.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e87e49674cf41ab4b461e71f4e2d4318fe9ba7fc8f5b8dc37fd852bdddaedc1b
-size 22374186
+oid sha256:5bd17df97803929936932ab8d32223b3c626309506f6a4c71b0237244f6d2177
+size 22374762

requirements.txt

@@ -1,3 +1,4 @@
+
 flask
 pandas
 scikit-learn