diff --git a/tinygrad/nn/state.py b/tinygrad/nn/state.py
index e0e2102852..f07004470b 100644
--- a/tinygrad/nn/state.py
+++ b/tinygrad/nn/state.py
@@ -2,7 +2,7 @@ import json, pathlib, zipfile, pickle, tarfile, struct, functools, io
 from typing import Dict, Union, List, Optional, Any, Tuple, Callable, BinaryIO, Iterable, TypeVar
 from tinygrad.tensor import Tensor
 from tinygrad.dtype import dtypes
-from tinygrad.helpers import prod, argsort, DEBUG, Timing, CI, unwrap, GlobalCounters, tqdm
+from tinygrad.helpers import prod, argsort, DEBUG, Timing, CI, unwrap, GlobalCounters, tqdm, round_up
 from tinygrad.shape.view import strides_for_shape
 from tinygrad.multi import MultiLazyBuffer
 
@@ -301,15 +301,15 @@ def gguf_load(tensor: Tensor) -> Tuple[Dict, Dict[str, Tensor]]:
   kv_data, state_dict = gguf_load(gguf_tensor)
   ```
   """
-  reader, kv_data, state_dict = io.BufferedReader(TensorIO(tensor), 1000_000), {}, {}
+  reader, kv_data, state_dict = io.BufferedReader(TensorIO(tensor), 1_000_000), {}, {}
   def read_unpack(fmt: str, n: int): return struct.unpack(fmt, reader.read(n))[0]
   def read_str(): return str(reader.read(read_uint64()), "utf-8")
   def read_arr():
     reader, n = readers[read_int32()], read_uint64()
     return [ reader() for _ in range(n) ]
 
-  readers: Dict[int, Callable[[], Any]] = { 8: read_str, 9: read_arr, **{ t: functools.partial(read_unpack, "<"+f, nb) for t, f, nb in [ (0,"c",1),
-    (1,"b",1), (2,"H",2), (3,"h",2), (4,"I",4), (5,"i",4), (6,"f",4), (7,"?",1), (10,"Q",8), (11,"q",8), (12,"d",8) ] } }
+  readers: Dict[int, Callable[[], Any]] = { 8: read_str, 9: read_arr, **{ t: functools.partial(read_unpack, "<"+f, nb) for t,f,nb in \
+    [ (0,"c",1), (1,"b",1), (2,"H",2), (3,"h",2), (4,"I",4), (5,"i",4), (6,"f",4), (7,"?",1), (10,"Q",8), (11,"q",8), (12,"d",8) ] } }
   read_uint32, read_int32, read_uint64, read_int64 = readers[4], readers[5], readers[10], readers[11]
 
   magic, version, n_tensors, n_kv = reader.read(4), read_int32(), read_int64(), read_int64()
@@ -320,7 +320,7 @@ def gguf_load(tensor: Tensor) -> Tuple[Dict, Dict[str, Tensor]]:
 
   t_infos = [ (read_str(), tuple(read_uint64() for _ in range(read_uint32())), read_int32(), read_uint64()) for _ in range(n_tensors) ]
   alignment, pos = kv_data.get("general.alignment", 32), reader.tell()
-  data_start = pos + (alignment - pos % alignment if pos % alignment != 0 else 0)
+  data_start = round_up(pos, alignment)
 
   for name, dims, typ, off in t_infos: state_dict[name] = ggml_data_to_tensor(tensor[data_start + off:], prod(dims), typ).reshape(*reversed(dims))