Auto-deploy from GitHub

models/detect.pt

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:dc0033a3face8e26aea12afad02f9471feca4264655ff081a2b05df0242d60a9
-size 52118546
+oid sha256:329114e15e99614491c1f49226c9bbffe7a94f2cfd1c77a9b7c0557c515292ec
+size 52112978

municipal_predictor.py

@@ -92,12 +92,10 @@ class DenguePredictor:
                 )
             df = pd.read_parquet(found)
         else:
-            hf_token = os.environ.get("HF_TOKEN")
             inference_path = hf_hub_download(
                 repo_id="previdengue/predict_inference_data",
                 filename="inference_data.parquet",
-                repo_type="dataset",
-                token=hf_token
+                repo_type="dataset"
             )
             df = pd.read_parquet(inference_path)
         df["codigo_ibge"] = df["codigo_ibge"].astype(int)

state_predictor.py

@@ -94,12 +94,10 @@ class StatePredictor:
             # Tenta baixar do HF; se falhar, tenta arquivo local como fallback
             df = None
             try:
-                hf_token = os.environ.get("HF_TOKEN")
                 inference_path = hf_hub_download(
-                    repo_id="previdengue/predict_inference_data",
+                    repo_id="previdengue/predict_inference_data_estadual",
                     filename="inference_data_estadual.parquet",
-                    repo_type="dataset",
-                    token=hf_token,
+                    repo_type="dataset"
                 )
                 df = pd.read_parquet(inference_path)
             except Exception: