run pre-commit

src/f5_tts/api.py

@@ -56,14 +56,20 @@ class F5TTS:
         if model_type == "F5-TTS":
             if not ckpt_file:
                 if mel_spec_type == "vocos":
-                    ckpt_file = str(cached_path("hf://SWivid/F5-TTS/F5TTS_Base/model_1200000.safetensors", cache_dir=local_path))
+                    ckpt_file = str(
+                        cached_path("hf://SWivid/F5-TTS/F5TTS_Base/model_1200000.safetensors", cache_dir=local_path)
+                    )
                 elif mel_spec_type == "bigvgan":
-                    ckpt_file = str(cached_path("hf://SWivid/F5-TTS/F5TTS_Base_bigvgan/model_1250000.pt", cache_dir=local_path))
+                    ckpt_file = str(
+                        cached_path("hf://SWivid/F5-TTS/F5TTS_Base_bigvgan/model_1250000.pt", cache_dir=local_path)
+                    )
             model_cfg = dict(dim=1024, depth=22, heads=16, ff_mult=2, text_dim=512, conv_layers=4)
             model_cls = DiT
         elif model_type == "E2-TTS":
             if not ckpt_file:
-                ckpt_file = str(cached_path("hf://SWivid/E2-TTS/E2TTS_Base/model_1200000.safetensors", cache_dir=local_path))
+                ckpt_file = str(
+                    cached_path("hf://SWivid/E2-TTS/E2TTS_Base/model_1200000.safetensors", cache_dir=local_path)
+                )
             model_cfg = dict(dim=1024, depth=24, heads=16, ff_mult=4)
             model_cls = UNetT
         else:

src/f5_tts/infer/utils_infer.py

@@ -96,8 +96,12 @@ def load_vocoder(vocoder_name="vocos", is_local=False, local_path="", device=dev
             print(f"Load vocos from local path {local_path}")
             repo_id = "charactr/vocos-mel-24khz"
             revision = None
-            config_path = hf_hub_download(repo_id=repo_id, cache_dir=local_path, filename="config.yaml", revision=revision)
-            model_path = hf_hub_download(repo_id=repo_id, cache_dir=local_path, filename="pytorch_model.bin", revision=revision)
+            config_path = hf_hub_download(
+                repo_id=repo_id, cache_dir=local_path, filename="config.yaml", revision=revision
+            )
+            model_path = hf_hub_download(
+                repo_id=repo_id, cache_dir=local_path, filename="pytorch_model.bin", revision=revision
+            )
             vocoder = Vocos.from_hparams(config_path=config_path)
             state_dict = torch.load(model_path, map_location="cpu")
             vocoder.load_state_dict(state_dict)