I copy-pasted the python script on this webpage for the bfloat16 model and removed device_map="auto" from model = AutoModelForCausalLM.from_pretrained(checkpoint, device_map="auto", torch_dtype=torch.bfloat16)
Then the script downloaded safetensors:

C:\Users\User\OneDrive\Desktop\SmolLM2>python bfloat16_SmolLM2_360_model.py
Downloading model.safetensors: 100%|████████████████████████████████████████████████| 724M/724M [01:02<00:00, 11.6MB/s]
C:\Users\User\AppData\Local\Programs\Python\Python311\Lib\site-packages\huggingface_hub\file_download.py:133: UserWarning: huggingface_hub cache-system uses symlinks by default to efficiently store duplicated files but your machine does not support them in C:\Users\User.cache\huggingface\hub. Caching files will still work but in a degraded version that might require more space on your disk. This warning can be disabled by setting the HF_HUB_DISABLE_SYMLINKS_WARNING environment variable. For more details, see https://huggingface.co/docs/huggingface_hub/how-to-cache#limitations.
To support symlinks on Windows, you either need to activate Developer Mode or to run Python as an administrator. In order to see activate developer mode, see this article: https://docs.microsoft.com/en-us/windows/apps/get-started/enable-your-device-for-development
warnings.warn(message)

Next, the script reported size mismatches:

C:\Users\User\OneDrive\Desktop\SmolLM2>python bfloat16_SmolLM2_360_model.py
Downloading model.safetensors: 100%|████████████████████████████████████████████████| 724M/724M [01:02<00:00, 11.6MB/s]
C:\Users\User\AppData\Local\Programs\Python\Python311\Lib\site-packages\huggingface_hub\file_download.py:133: UserWarning: huggingface_hub cache-system uses symlinks by default to efficiently store duplicated files but your machine does not support them in C:\Users\User.cache\huggingface\hub. Caching files will still work but in a degraded version that might require more space on your disk. This warning can be disabled by setting the HF_HUB_DISABLE_SYMLINKS_WARNING environment variable. For more details, see https://huggingface.co/docs/huggingface_hub/how-to-cache#limitations.
To support symlinks on Windows, you either need to activate Developer Mode or to run Python as an administrator. In order to see activate developer mode, see this article: https://docs.microsoft.com/en-us/windows/apps/get-started/enable-your-device-for-development
warnings.warn(message)

A module that was compiled using NumPy 1.x cannot be run in
NumPy 2.1.3 as it may crash. To support both 1.x and 2.x
versions of NumPy, modules must be compiled with NumPy 2.0.
Some module may need to rebuild instead e.g. with 'pybind11>=2.12'.

If you are a user of the module, the easiest solution will be to
downgrade to 'numpy<2' or try to upgrade the affected module.
We expect that some modules will need time to support NumPy 2.

Traceback (most recent call last): File "C:\Users\User\OneDrive\Desktop\SmolLM2\bfloat16_SmolLM2_360_model.py", line 12, in
model = AutoModelForCausalLM.from_pretrained(checkpoint, torch_dtype=torch.bfloat16)
File "C:\Users\User\AppData\Local\Programs\Python\Python311\Lib\site-packages\transformers\models\auto\auto_factory.py", line 484, in from_pretrained
return model_class.from_pretrained(
File "C:\Users\User\AppData\Local\Programs\Python\Python311\Lib\site-packages\transformers\modeling_utils.py", line 2604, in from_pretrained
state_dict = load_state_dict(resolved_archive_file)
File "C:\Users\User\AppData\Local\Programs\Python\Python311\Lib\site-packages\transformers\modeling_utils.py", line 461, in load_state_dict
return safe_load_file(checkpoint_file)
File "C:\Users\User\AppData\Local\Programs\Python\Python311\Lib\site-packages\safetensors\torch.py", line 261, in load_file
result[k] = f.get_tensor(k)
File "C:\Users\User\AppData\Local\Programs\Python\Python311\Lib\site-packages\torch\storage.py", line 234, in getitem
return super().getitem(*args, **kwargs)
C:\Users\User\AppData\Local\Programs\Python\Python311\Lib\site-packages\torch\storage.py:234: UserWarning: Failed to initialize NumPy: _ARRAY_API not found (Triggered internally at ..\torch\csrc\utils\tensor_numpy.cpp:84.)
return super().getitem(*args, **kwargs)
Traceback (most recent call last):
File "C:\Users\User\OneDrive\Desktop\SmolLM2\bfloat16_SmolLM2_360_model.py", line 12, in
model = AutoModelForCausalLM.from_pretrained(checkpoint, torch_dtype=torch.bfloat16)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\User\AppData\Local\Programs\Python\Python311\Lib\site-packages\transformers\models\auto\auto_factory.py", line 484, in from_pretrained
return model_class.from_pretrained(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\User\AppData\Local\Programs\Python\Python311\Lib\site-packages\transformers\modeling_utils.py", line 2881, in from_pretrained
) = cls._load_pretrained_model(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\User\AppData\Local\Programs\Python\Python311\Lib\site-packages\transformers\modeling_utils.py", line 3278, in _load_pretrained_model
raise RuntimeError(f"Error(s) in loading state_dict for {model.class.name}:\n\t{error_msg}")
RuntimeError: Error(s) in loading state_dict for LlamaForCausalLM:
size mismatch for model.layers.0.self_attn.k_proj.weight: copying a param with shape torch.Size([320, 960]) from checkpoint, the shape in current model is torch.Size([960, 960]).
size mismatch for model.layers.0.self_attn.v_proj.weight: copying a param with shape torch.Size([320, 960]) from checkpoint, the shape in current model is torch.Size([960, 960]).
size mismatch for model.layers.1.self_attn.k_proj.weight: copying a param with shape torch.Size([320, 960]) from checkpoint, the shape in current model is torch.Size([960, 960]).
size mismatch for model.layers.1.self_a
[[ etcetera]]
size mismatch for model.layers.31.self_attn.k_proj.weight: copying a param with shape torch.Size([320, 960]) from checkpoint, the shape in current model is torch.Size([960, 960]).
size mismatch for model.layers.31.self_attn.v_proj.weight: copying a param with shape torch.Size([320, 960]) from checkpoint, the shape in current model is torch.Size([960, 960]).
You may consider adding ignore_mismatched_sizes=True in the model from_pretrained method.

C:\Users\User\OneDrive\Desktop\SmolLM2>