Upload folder using huggingface_hub

clustering_features.json

@@ -0,0 +1,14 @@
+[
+  "Median_Income",
+  "Poverty_Rate",
+  "PCT_65OLDER10",
+  "PCT_18YOUNGER10",
+  "PCT_HISP10",
+  "PCT_NHBLACK10",
+  "FOODINSEC_13_15",
+  "Farmers_Markets_Count_16",
+  "FMRKTPTH16",
+  "PCT_LOCLFARM12",
+  "PC_DIRSALES12",
+  "PCH_VEG_ACRESPTH_07_12"
+]

kmeans_model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:48fae174d305232a7cafc71edf43ae3da6797041dc8a2dc8ca31ea3e2d2535fd
+size 14019

scaler.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b4eba40a19091872d58c22d288cd4982422ffe14d1e216463ec1c94f64bb5a36
+size 1447

upload_models.py

@@ -0,0 +1,20 @@
+from huggingface_hub import login, HfApi, upload_folder
+
+# 1️⃣ Connecte-toi avec ton token Hugging Face
+# Remplace "TON_ACCESS_TOKEN_ICI" par ton vrai token
+login("TON_ACCESS_TOKEN_ICI")
+
+# 2️⃣ Crée le repo sur Hugging Face (facultatif si déjà créé)
+api = HfApi()
+repo_name = "us-foodscope-model"
+username = "TON_USERNAME_HF"  # remplace par ton nom HF
+api.create_repo(repo_id=f"{username}/{repo_name}", repo_type="model", exist_ok=True)
+
+# 3️⃣ Uploader tous les fichiers du dossier courant
+upload_folder(
+    folder_path=".",  # le dossier où sont tes .pkl/.joblib
+    repo_id=f"{username}/{repo_name}",
+    repo_type="model"
+)
+
+print("✅ Upload terminé !")

xgboost_tuned_model.joblib

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9af897848550f5db83d08be75fa91c8c698f142e08571f82586aa2186224c67b
+size 123431