[Bug]: webui无法切换大模型

[qinshao99]

Checklist

• The issue exists after disabling all extensions
• The issue exists on a clean installation of webui
• The issue is caused by an extension, but I believe it is caused by a bug in the webui
• The issue exists in the current version of the webui
• The issue has not been reported before recently
• The issue has been reported before but has not been fixed yet

What happened?

webui切换大模型 不成功，只能使用 安装的时候 自带的大模型

Steps to reproduce the problem

1、Stable Diffusion 模型 选择 sd3_medium.safetensors 模型，处理几秒后，会自动切回v1-5-pruned-emaonly.safetensors 这个模型

What should have happened?

Stable Diffusion 模型切换不成功

What browsers do you use to access the UI ?

Google Chrome

Sysinfo

sysinfo-2024-12-23-12-29.json

Console logs

Applying attention optimization: Doggettx... done.
Model loaded in 10.2s (load weights from disk: 0.7s, create model: 0.5s, apply weights to model: 7.7s, apply fp8: 0.7s, calculate empty prompt: 0.4s).

To create a public link, set `share=True` in `launch()`.
🤯 LobeTheme: Initializing...
Startup time: 65.8s (prepare environment: 30.9s, import torch: 4.5s, import gradio: 1.2s, setup paths: 2.9s, initialize shared: 0.5s, other imports: 0.5s, load scripts: 7.0s, create ui: 1.2s, gradio launch: 16.9s).
Reusing loaded model v1-5-pruned-emaonly.safetensors [6ce0161689] to load sd3_medium.safetensors [cc236278d2]
Loading weights [cc236278d2] from G:\sd\stable-diffusion-webui-1.10.0\models\Stable-diffusion\sd3_medium.safetensors
Creating model from config: G:\sd\stable-diffusion-webui-1.10.0\configs\sd3-inference.yaml
creating model quickly: TypeError
Traceback (most recent call last):
  File "D:\python\lib\threading.py", line 973, in _bootstrap
    self._bootstrap_inner()
  File "D:\python\lib\threading.py", line 1016, in _bootstrap_inner
    self.run()
  File "G:\sd\stable-diffusion-webui-1.10.0\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 807, in run
    result = context.run(func, *args)
  File "G:\sd\stable-diffusion-webui-1.10.0\venv\lib\site-packages\gradio\utils.py", line 707, in wrapper
    response = f(*args, **kwargs)
  File "G:\sd\stable-diffusion-webui-1.10.0\modules\ui_settings.py", line 316, in <lambda>
    fn=lambda value, k=k: self.run_settings_single(value, key=k),
  File "G:\sd\stable-diffusion-webui-1.10.0\modules\ui_settings.py", line 95, in run_settings_single
    if value is None or not opts.set(key, value):
  File "G:\sd\stable-diffusion-webui-1.10.0\modules\options.py", line 165, in set
    option.onchange()
  File "G:\sd\stable-diffusion-webui-1.10.0\modules\call_queue.py", line 14, in f
    res = func(*args, **kwargs)
  File "G:\sd\stable-diffusion-webui-1.10.0\modules\initialize_util.py", line 181, in <lambda>
    shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: sd_models.reload_model_weights()), call=False)
  File "G:\sd\stable-diffusion-webui-1.10.0\modules\sd_models.py", line 977, in reload_model_weights
    load_model(checkpoint_info, already_loaded_state_dict=state_dict)
  File "G:\sd\stable-diffusion-webui-1.10.0\modules\sd_models.py", line 820, in load_model
    sd_model = instantiate_from_config(sd_config.model, state_dict)
  File "G:\sd\stable-diffusion-webui-1.10.0\modules\sd_models.py", line 775, in instantiate_from_config
    return constructor(**params)
  File "G:\sd\stable-diffusion-webui-1.10.0\modules\models\sd3\sd3_model.py", line 34, in __init__
    self.text_encoders = SD3Cond()
  File "G:\sd\stable-diffusion-webui-1.10.0\modules\models\sd3\sd3_cond.py", line 164, in __init__
    self.tokenizer = SD3Tokenizer()
  File "G:\sd\stable-diffusion-webui-1.10.0\modules\models\sd3\other_impls.py", line 221, in __init__
    self.t5xxl = T5XXLTokenizer()
  File "G:\sd\stable-diffusion-webui-1.10.0\modules\models\sd3\other_impls.py", line 317, in __init__
    super().__init__(pad_with_end=False, tokenizer=T5TokenizerFast.from_pretrained("google/t5-v1_1-xxl"), has_start_token=False, pad_to_max_length=False, max_length=99999999, min_length=77)
  File "G:\sd\stable-diffusion-webui-1.10.0\venv\lib\site-packages\transformers\tokenization_utils_base.py", line 1825, in from_pretrained
    return cls._from_pretrained(
  File "G:\sd\stable-diffusion-webui-1.10.0\venv\lib\site-packages\transformers\tokenization_utils_base.py", line 1988, in _from_pretrained
    tokenizer = cls(*init_inputs, **init_kwargs)
  File "G:\sd\stable-diffusion-webui-1.10.0\venv\lib\site-packages\transformers\models\t5\tokenization_t5_fast.py", line 133, in __init__
    super().__init__(
  File "G:\sd\stable-diffusion-webui-1.10.0\venv\lib\site-packages\transformers\tokenization_utils_fast.py", line 114, in __init__
    fast_tokenizer = convert_slow_tokenizer(slow_tokenizer)
  File "G:\sd\stable-diffusion-webui-1.10.0\venv\lib\site-packages\transformers\convert_slow_tokenizer.py", line 1307, in convert_slow_tokenizer
    return converter_class(transformer_tokenizer).converted()
  File "G:\sd\stable-diffusion-webui-1.10.0\venv\lib\site-packages\transformers\convert_slow_tokenizer.py", line 445, in __init__
    from .utils import sentencepiece_model_pb2 as model_pb2
  File "G:\sd\stable-diffusion-webui-1.10.0\venv\lib\site-packages\transformers\utils\sentencepiece_model_pb2.py", line 91, in <module>
    _descriptor.EnumValueDescriptor(
  File "G:\sd\stable-diffusion-webui-1.10.0\venv\lib\site-packages\google\protobuf\descriptor.py", line 920, in __new__
    _message.Message._CheckCalledFromGeneratedFile()
TypeError: Descriptors cannot be created directly.
If this call came from a _pb2.py file, your generated code is out of date and must be regenerated with protoc >= 3.19.0.
If you cannot immediately regenerate your protos, some other possible workarounds are:
 1. Downgrade the protobuf package to 3.20.x or lower.
 2. Set PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python (but this will use pure-Python parsing and will be much slower).

More information: https://developers.google.com/protocol-buffers/docs/news/2022-05-06#python-updates

Failed to create model quickly; will retry using slow method.
changing setting sd_model_checkpoint to sd3_medium.safetensors [cc236278d2]: TypeError
Traceback (most recent call last):
  File "G:\sd\stable-diffusion-webui-1.10.0\modules\options.py", line 165, in set
    option.onchange()
  File "G:\sd\stable-diffusion-webui-1.10.0\modules\call_queue.py", line 14, in f
    res = func(*args, **kwargs)
  File "G:\sd\stable-diffusion-webui-1.10.0\modules\initialize_util.py", line 181, in <lambda>
    shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: sd_models.reload_model_weights()), call=False)
  File "G:\sd\stable-diffusion-webui-1.10.0\modules\sd_models.py", line 977, in reload_model_weights
    load_model(checkpoint_info, already_loaded_state_dict=state_dict)
  File "G:\sd\stable-diffusion-webui-1.10.0\modules\sd_models.py", line 829, in load_model
    sd_model = instantiate_from_config(sd_config.model, state_dict)
  File "G:\sd\stable-diffusion-webui-1.10.0\modules\sd_models.py", line 775, in instantiate_from_config
    return constructor(**params)
  File "G:\sd\stable-diffusion-webui-1.10.0\modules\models\sd3\sd3_model.py", line 34, in __init__
    self.text_encoders = SD3Cond()
  File "G:\sd\stable-diffusion-webui-1.10.0\modules\models\sd3\sd3_cond.py", line 164, in __init__
    self.tokenizer = SD3Tokenizer()
  File "G:\sd\stable-diffusion-webui-1.10.0\modules\models\sd3\other_impls.py", line 221, in __init__
    self.t5xxl = T5XXLTokenizer()
  File "G:\sd\stable-diffusion-webui-1.10.0\modules\models\sd3\other_impls.py", line 317, in __init__
    super().__init__(pad_with_end=False, tokenizer=T5TokenizerFast.from_pretrained("google/t5-v1_1-xxl"), has_start_token=False, pad_to_max_length=False, max_length=99999999, min_length=77)
  File "G:\sd\stable-diffusion-webui-1.10.0\venv\lib\site-packages\transformers\tokenization_utils_base.py", line 1825, in from_pretrained
    return cls._from_pretrained(
  File "G:\sd\stable-diffusion-webui-1.10.0\venv\lib\site-packages\transformers\tokenization_utils_base.py", line 1988, in _from_pretrained
    tokenizer = cls(*init_inputs, **init_kwargs)
  File "G:\sd\stable-diffusion-webui-1.10.0\venv\lib\site-packages\transformers\models\t5\tokenization_t5_fast.py", line 133, in __init__
    super().__init__(
  File "G:\sd\stable-diffusion-webui-1.10.0\venv\lib\site-packages\transformers\tokenization_utils_fast.py", line 114, in __init__
    fast_tokenizer = convert_slow_tokenizer(slow_tokenizer)
  File "G:\sd\stable-diffusion-webui-1.10.0\venv\lib\site-packages\transformers\convert_slow_tokenizer.py", line 1307, in convert_slow_tokenizer
    return converter_class(transformer_tokenizer).converted()
  File "G:\sd\stable-diffusion-webui-1.10.0\venv\lib\site-packages\transformers\convert_slow_tokenizer.py", line 445, in __init__
    from .utils import sentencepiece_model_pb2 as model_pb2
  File "G:\sd\stable-diffusion-webui-1.10.0\venv\lib\site-packages\transformers\utils\sentencepiece_model_pb2.py", line 28, in <module>
    DESCRIPTOR = _descriptor.FileDescriptor(
  File "G:\sd\stable-diffusion-webui-1.10.0\venv\lib\site-packages\google\protobuf\descriptor.py", line 1228, in __new__
    return _message.default_pool.AddSerializedFile(serialized_pb)
TypeError: Couldn't build proto file into descriptor pool: duplicate file name sentencepiece_model.proto

Additional information

电脑安装了forgeui

[Archkon]

Try Downgrading the protobuf package to 3.20.x or lower.