---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[5], line 13
     10 model_path = "/mnt/models/AI-ModelScope/stable-diffusion-3.5-large-turbo"
     11 torch_dtype = torch.float16
---> 13 transformer = SD3Transformer2DModel.from_pretrained(
     14     model_path,
     15     subfolder="transformer",
     16     quantization_config=BitsAndBytesConfig(
     17         load_in_4bit=True,
     18         bnb_4bit_quant_type="nf4",
     19         bnb_4bit_compute_dtype=torch.bfloat16,
     20         bnb_4bit_use_double_quant=True
     21     ),
     22     torch_dtype=torch_dtype
     23 )
     24 text_encoder = CLIPTextModelWithProjection.from_pretrained(
     25     model_path,
     26     subfolder="text_encoder",
   (...)     33     torch_dtype=torch_dtype
     34 )
     35 text_encoder_2 = CLIPTextModelWithProjection.from_pretrained(
     36     model_path,
     37     subfolder="text_encoder_2",
   (...)     44     torch_dtype=torch_dtype
     45 )

File ~/python_project/StoryFusion/.venv/lib/python3.12/site-packages/huggingface_hub/utils/_validators.py:114, in validate_hf_hub_args.<locals>._inner_fn(*args, **kwargs)
    111 if check_use_auth_token:
    112     kwargs = smoothly_deprecate_use_auth_token(fn_name=fn.__name__, has_token=has_token, kwargs=kwargs)
--> 114 return fn(*args, **kwargs)

File ~/python_project/StoryFusion/.venv/lib/python3.12/site-packages/diffusers/models/modeling_utils.py:1206, in ModelMixin.from_pretrained(cls, pretrained_model_name_or_path, **kwargs)
   1196 if hf_quantizer is not None:
   1197     hf_quantizer.validate_environment(device_map=device_map)
   1199 (
   1200     model,
   1201     missing_keys,
   1202     unexpected_keys,
   1203     mismatched_keys,
   1204     offload_index,
   1205     error_msgs,
-> 1206 ) = cls._load_pretrained_model(
   1207     model,
   1208     state_dict,
   1209     resolved_model_file,
   1210     pretrained_model_name_or_path,
   1211     loaded_keys,
   1212     ignore_mismatched_sizes=ignore_mismatched_sizes,
   1213     low_cpu_mem_usage=low_cpu_mem_usage,
   1214     device_map=device_map,
   1215     offload_folder=offload_folder,
   1216     offload_state_dict=offload_state_dict,
   1217     dtype=torch_dtype,
   1218     hf_quantizer=hf_quantizer,
   1219     keep_in_fp32_modules=keep_in_fp32_modules,
   1220     dduf_entries=dduf_entries,
   1221 )
   1222 loading_info = {
   1223     "missing_keys": missing_keys,
   1224     "unexpected_keys": unexpected_keys,
   1225     "mismatched_keys": mismatched_keys,
   1226     "error_msgs": error_msgs,
   1227 }
   1229 # Dispatch model with hooks on all devices if necessary

File ~/python_project/StoryFusion/.venv/lib/python3.12/site-packages/diffusers/models/modeling_utils.py:1465, in ModelMixin._load_pretrained_model(cls, model, state_dict, resolved_model_file, pretrained_model_name_or_path, loaded_keys, ignore_mismatched_sizes, assign_to_params_buffers, hf_quantizer, low_cpu_mem_usage, dtype, keep_in_fp32_modules, device_map, offload_state_dict, offload_folder, dduf_entries)
   1457 mismatched_keys += _find_mismatched_keys(
   1458     state_dict,
   1459     model_state_dict,
   1460     loaded_keys,
   1461     ignore_mismatched_sizes,
   1462 )
   1464 if low_cpu_mem_usage:
-> 1465     offload_index, state_dict_index = load_model_dict_into_meta(
   1466         model,
   1467         state_dict,
   1468         device_map=device_map,
   1469         dtype=dtype,
   1470         hf_quantizer=hf_quantizer,
   1471         keep_in_fp32_modules=keep_in_fp32_modules,
   1472         unexpected_keys=unexpected_keys,
   1473         offload_folder=offload_folder,
   1474         offload_index=offload_index,
   1475         state_dict_index=state_dict_index,
   1476         state_dict_folder=state_dict_folder,
   1477     )
   1478 else:
   1479     if assign_to_params_buffers is None:

File ~/python_project/StoryFusion/.venv/lib/python3.12/site-packages/diffusers/models/model_loading_utils.py:298, in load_model_dict_into_meta(model, state_dict, dtype, model_name_or_path, hf_quantizer, keep_in_fp32_modules, device_map, unexpected_keys, offload_folder, offload_index, state_dict_index, state_dict_folder)
    294     state_dict_index = offload_weight(param, param_name, state_dict_folder, state_dict_index)
    295 elif is_quantized and (
    296     hf_quantizer.check_if_quantized_param(model, param, param_name, state_dict, param_device=param_device)
    297 ):
--> 298     hf_quantizer.create_quantized_param(
    299         model, param, param_name, param_device, state_dict, unexpected_keys, dtype=dtype
    300     )
    301 else:
    302     set_module_tensor_to_device(model, param_name, param_device, value=param, **set_module_kwargs)

TypeError: BnB4BitDiffusersQuantizer.create_quantized_param() got an unexpected keyword argument 'dtype'