Upload app.py with huggingface_hub

app.py

@@ -4,9 +4,15 @@ import torch.nn as nn
 from transformers import AutoModel, AutoTokenizer
 from peft import LoraConfig, get_peft_model
 import numpy as np
+import os
+from huggingface_hub import hf_hub_download
 
 device = torch.device('cpu') # HF Free Tier uses CPU
-ckpt = torch.load("AyurGenixV9_FULLY_EMBEDDED.pt", map_location=device, weights_only=False)
+
+# DOWNLOAD THE HUGE MODEL FROM YOUR MODEL REPO INSTEAD OF LOCAL STORAGE
+print("Downloading heavy model weights from hnninioi/AyurGenixV9-Model...")
+model_path = hf_hub_download(repo_id="hnninioi/AyurGenixV9-Model", filename="AyurGenixV9_FULLY_EMBEDDED.pt")
+ckpt = torch.load(model_path, map_location=device, weights_only=False)
 
 cfg = ckpt['config']
 all_herbs = ckpt['all_herbs']