size mismatch error

[Shobhit1201]

RuntimeError: Error(s) in loading state_dict for NougatModel:
size mismatch for encoder.model.layers.1.downsample.norm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for encoder.model.layers.1.downsample.norm.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for encoder.model.layers.1.downsample.reduction.weight: copying a param with shape torch.Size([512, 1024]) from checkpoint, the shape in current model is torch.Size([256, 512]).
size mismatch for encoder.model.layers.2.downsample.norm.weight: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.model.layers.2.downsample.norm.bias: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.model.layers.2.downsample.reduction.weight: copying a param with shape torch.Size([1024, 2048]) from checkpoint, the shape in current model is torch.Size([512, 1024]).
You may consider adding ignore_mismatched_sizes=True in the model from_pretrained method.

i am working in google colab. Already tried updating timm.
and where is the requirements file for this repo?

[tobiaswuerth]

I get the same error:

(.venv) PS D:\rolling_embedding> nougat "D:\rolling_embedding\arxiv_downloads\0808.2870_measuring_distance_and_properties_of_the_milky_way_s_central_supermassive_black_hole_with_stellar_orbits.pdf" -o "D:\rolling_embedding\arxiv_downloads\test" -m 0.1.0-base
Traceback (most recent call last):
  File "<frozen runpy>", line 198, in _run_module_as_main
  File "<frozen runpy>", line 88, in _run_code
  File "D:\rolling_embedding\.venv\Scripts\nougat.exe\__main__.py", line 7, in <module>
  File "D:\rolling_embedding\.venv\Lib\site-packages\predict.py", line 127, in main
    model = NougatModel.from_pretrained(args.checkpoint)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:\rolling_embedding\.venv\Lib\site-packages\nougat\model.py", line 684, in from_pretrained
    model = super(NougatModel, cls).from_pretrained(
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:\rolling_embedding\.venv\Lib\site-packages\transformers\modeling_utils.py", line 279, in _wrapper
    return func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^
  File "D:\rolling_embedding\.venv\Lib\site-packages\transformers\modeling_utils.py", line 4400, in from_pretrained
    ) = cls._load_pretrained_model(
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:\rolling_embedding\.venv\Lib\site-packages\transformers\modeling_utils.py", line 4829, in _load_pretrained_model
    disk_offload_index, cpu_offload_index = _load_state_dict_into_meta_model(
                                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:\rolling_embedding\.venv\Lib\site-packages\torch\utils\_contextlib.py", line 116, in decorate_context
    return func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^
  File "D:\rolling_embedding\.venv\Lib\site-packages\transformers\modeling_utils.py", line 824, in _load_state_dict_into_meta_model
    _load_parameter_into_model(model, param_name, param.to(param_device))
  File "D:\rolling_embedding\.venv\Lib\site-packages\transformers\modeling_utils.py", line 712, in _load_parameter_into_model
    module.load_state_dict({param_type: tensor}, strict=False, assign=True)
  File "D:\rolling_embedding\.venv\Lib\site-packages\torch\nn\modules\module.py", line 2581, in load_state_dict
    raise RuntimeError(
RuntimeError: Error(s) in loading state_dict for Linear:
        size mismatch for weight: copying a param with shape torch.Size([512, 1024]) from checkpoint, the shape in current model is torch.Size([256, 512]).