Support Hugging Face models (#215)

* support hf direct models

whisper/convert.py

@@ -71,7 +71,9 @@ def _download(url: str, root: str) -> str:
         if hashlib.sha256(model_bytes).hexdigest() == expected_sha256:
             return download_target
         else:
-            warnings.warn(f"{download_target} exists, but the SHA256 checksum does not match; re-downloading the file")
+            warnings.warn(
+                f"{download_target} exists, but the SHA256 checksum does not match; re-downloading the file"
+            )
 
     with urllib.request.urlopen(url) as source, open(download_target, "wb") as output:
         with tqdm(
@@ -132,7 +134,9 @@ def load_torch_model(
         alignment_heads = _ALIGNMENT_HEADS[name_or_path]
         name_or_path = _download(_MODELS[name_or_path], download_root)
     elif not Path(name_or_path).is_file():
-        raise RuntimeError(f"Model {name_or_path} is neither found in {available_models()} nor as a local path")
+        raise RuntimeError(
+            f"Model {name_or_path} is neither found in {available_models()} nor as a local path"
+        )
 
     with open(name_or_path, "rb") as fp:
         checkpoint = torch.load(fp)
@@ -259,7 +263,9 @@ if __name__ == "__main__":
     )
     args = parser.parse_args()
 
-    assert args.dtype in _VALID_DTYPES, f"dtype {args.dtype} not found in {_VALID_DTYPES}"
+    assert (
+        args.dtype in _VALID_DTYPES
+    ), f"dtype {args.dtype} not found in {_VALID_DTYPES}"
     dtype = getattr(mx, args.dtype)
 
     print("[INFO] Loading")