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app.py

@@ -17,32 +17,23 @@ MODEL_REPO = "GAASH-Lab/Matcha-TTS-Kashmiri"
 def load_models():
     print("[*] Downloading GAASH-Lab checkpoint...")
     ckpt = hf_hub_download(repo_id=MODEL_REPO, filename="model.ckpt", token=HF_TOKEN)
-    
-    # Load Matcha
     model = MatchaTTS.load_from_checkpoint(ckpt, map_location=DEVICE, weights_only=False)
     model.eval()
-      
-    print("[*] Downloading HiFi-GAN vocoder...")
-    # FIX: Use the correct repository ID and filename
-    # Many Matcha-TTS setups use 'shivammehta25/Matcha-TTS' or specific vocoder repos
-    try:
-        vocoder_ckpt = hf_hub_download(repo_id="shivammehta25/Matcha-TTS", filename="hifigan_v1")
-    except Exception:
-        # Fallback to another common public HiFi-GAN checkpoint if the above is unavailable
-        vocoder_ckpt = hf_hub_download(repo_id="jaketae/hifigan-lj-v1", filename="generator.pth")
+    
+    print("[*] Loading HiFi-GAN vocoder...")
+    # The file 'generator_v1' is what the code calls 'hifigan_T2_v1'
+    # We download it from the official GitHub release if not found locally
+    vocoder_path = Path("hifigan_T2_v1")
+    if not vocoder_path.exists():
+        url = "https://github.com/shivammehta25/Matcha-TTS-checkpoints/releases/download/v1.0/generator_v1"
+        urllib.request.urlretrieve(url, vocoder_path)
 
     vocoder = HiFiGAN(AttrDict(v1)).to(DEVICE)
-    
-    # Load state dict
-    state_dict = torch.load(vocoder_ckpt, map_location=DEVICE)
-    # HiFi-GAN checkpoints usually store the weights under the 'generator' key
-    if 'generator' in state_dict:
-        vocoder.load_state_dict(state_dict['generator'])
-    else:
-        vocoder.load_state_dict(state_dict)
-        
+    state_dict = torch.load(vocoder_path, map_location=DEVICE)
+    vocoder.load_state_dict(state_dict['generator'])
     vocoder.eval()
     vocoder.remove_weight_norm()
+    
     return model, vocoder
 
 model, vocoder = load_models()