报错:Loading model from checkpoints/FLIR.ckpt Global Step: 1300 LatentDiffusion: Running in eps-prediction mode DiffusionWrapper has 859.54 M params. Keeping EMAs of 688. making attention of type 'vanilla' with 512 in_channels Working with z of shape (1, 4, 32, 32) = 4096 dimensions. making attention of type 'vanilla' with 512 in_channels Traceback (most recent call last): File "E:\work\Python3\Lib\site-packages\transformers\utils\hub.py", line 470, in cached_files hf_hub_download( File "E:\work\Python3\Lib\site-packages\huggingface_hub\utils\_validators.py", line 106, in _inner_fn validate_repo_id(arg_value) File "E:\work\Python3\Lib\site-packages\huggingface_hub\utils\_validators.py", line 154, in validate_repo_id raise HFValidationError( huggingface_hub.errors.HFValidationError: Repo id must be in the form 'repo_name' or 'namespace/repo_name': '/data/wld/ip2p/clip-vit-large-patch14/'. Use `repo_type` argument if needed. During handling of the above exception, another exception occurred: Traceback (most recent call last): File "E:\work\Python3\Lib\site-packages\transformers\tokenization_utils_base.py", line 1923, in from_pretrained resolved_config_file = cached_file( ^^^^^^^^^^^^ File "E:\work\Python3\Lib\site-packages\transformers\utils\hub.py", line 312, in cached_file file = cached_files(path_or_repo_id=path_or_repo_id, filenames=[filename], **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "E:\work\Python3\Lib\site-packages\transformers\utils\hub.py", line 523, in cached_files _get_cache_file_to_return(path_or_repo_id, filename, cache_dir, revision) for filename in full_filenames ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "E:\work\Python3\Lib\site-packages\transformers\utils\hub.py", line 140, in _get_cache_file_to_return resolved_file = try_to_load_from_cache(path_or_repo_id, full_filename, cache_dir=cache_dir, revision=revision) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "E:\work\Python3\Lib\site-packages\huggingface_hub\utils\_validators.py", line 106, in _inner_fn validate_repo_id(arg_value) File "E:\work\Python3\Lib\site-packages\huggingface_hub\utils\_validators.py", line 154, in validate_repo_id raise HFValidationError( huggingface_hub.errors.HFValidationError: Repo id must be in the form 'repo_name' or 'namespace/repo_name': '/data/wld/ip2p/clip-vit-large-patch14/'. Use `repo_type` argument if needed. During handling of the above exception, another exception occurred: Traceback (most recent call last): File "F:\AI\DiffV2IR\infer.py", line 182, in <module> File "F:\AI\DiffV2IR\infer.py", line 118, in main model.eval().cuda() ^^^^^^^^^^^^ File "F:\AI\DiffV2IR\infer.py", line 74, in load_model_from_config m, u = model.load_state_dict(sd, strict=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "F:\AI/DiffV2IR/git-package\stable_diffusion\ldm\util.py", line 85, in instantiate_from_config return get_obj_from_str(config["target"])(**config.get("params", dict())) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "F:\AI\DiffV2IR\ldm\models\diffusion\ddpm_DiffV2IR.py", line 517, in __init__ self.instantiate_cond_stage(cond_stage_config) File "F:\AI\DiffV2IR\ldm\models\diffusion\ddpm_DiffV2IR.py", line 579, in instantiate_cond_stage model = instantiate_from_config(config) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "F:\AI\DiffV2IR\ldm\util.py", line 85, in instantiate_from_config return get_obj_from_str(config["target"])(**config.get("params", dict())) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "F:\AI\DiffV2IR\ldm\modules\encoders\modules.py", line 141, in __init__ self.tokenizer = CLIPTokenizer.from_pretrained(version) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "E:\work\Python3\Lib\site-packages\transformers\tokenization_utils_base.py", line 1943, in from_pretrained raise OSError( OSError: Can't load tokenizer for '/data/wld/ip2p/clip-vit-large-patch14/'. If you were trying to load it from 'https://huggingface.co/models', make sure you don't have a local directory with the same name. Otherwise, make sure '/data/wld/ip2p/clip-vit-large-patch14/' is the correct path to a directory containing all relevant files for a CLIPTokenizer tokenizer.
时间: 2025-05-28 07:59:47 浏览: 130
<think>嗯,我现在遇到了一个错误,需要仔细看看。错误信息显示在加载模型的时候出了问题,特别是关于CLIPTokenizer的加载失败。首先,错误提示说Repoid必须是'repo_name'或'namespace/repo_name'的格式,但当前路径是'/data/wld/ip2p/clip-vit-large-patch14/'。看起来程序在尝试从HuggingFaceHub下载模型或分词器,但给出的路径不符合要求。看错误堆栈,问题出在from_pretrained方法调用的时候。代码里可能指定了一个本地路径,但该路径不存在或者格式不正确。例如,在实例化CLIPTokenizer时,使用了version变量,而这个变量可能被错误地设置成了本地路径,而不是正确的HuggingFace模型名称。可能的原因是配置文件中的路径被硬编码为绝对路径,比如/data/wld/...,但实际运行时这个路径在用户的机器上不存在。例如,在cond_stage_config里,可能指定了target为某个类,并且params中的version是那个绝对路径。这时候,当程序尝试加载分词器时,HuggingFace的库会认为这是一个repoid,但路径不符合规范,所以报错。解决办法应该是修改配置文件,将version从绝对路径改为正确的HuggingFace模型名称,比如"openai/clip-vit-large-patch14"。或者,如果确实需要使用本地模型,确保路径正确,并且所有必要的文件都存在。另外,检查是否在本地有一个名为'/data/wld/ip2p/clip-vit-large-patch14/'的目录,如果没有,可能需要下载模型文件到正确的路径,或者更改配置指向正确的本地或远程路径。例如,在代码中,可能有一个地方设置了version='/data/wld/ip2p/clip-vit-large-patch14/',需要将其改为正确的模型名称,如"openai/clip-vit-large-patch14"。同时,确保网络连接正常,可以访问HuggingFaceHub下载所需的模型文件。如果用户无法修改配置文件,可能需要通过环境变量或运行时参数来覆盖该路径。或者,检查是否有环境变量或配置文件中的路径被错误地设置成了绝对路径,导致程序在加载时出错。总结来说,问题核心在于模型或分词器的路径配置错误,导致HuggingFace库无法正确加载。需要修正路径为有效的模型标识符或正确的本地路径。</think>这个错误发生在尝试加载`CLIPTokenizer`时,Hugging Face库无法正确解析模型路径。根本原因是配置中使用了不符合Hugging Face规范的路径格式。
**解决方法**:
```python
# 修改CLIPTokenizer的加载方式,使用标准Hugging Face模型名称
from transformers import CLIPTokenizer
# 正确格式的模型名称
version = "openai/clip-vit-large-patch14" # 替换错误的绝对路径
tokenizer = CLIPTokenizer.from_pretrained(version)
# 或者指定正确的本地路径(如果使用离线模型)
local_path = "./models/clip-vit-large-patch14" # 确保包含所有必要文件
tokenizer = CLIPTokenizer.from_pretrained(local_path)
```
**错误原因**:
1. 路径格式错误:代码中使用了`/data/wld/ip2p/clip-vit-large-patch14/`这样的绝对路径,Hugging Face库会将其误认为无效的repo ID
2. 文件缺失:指定的路径中可能缺少tokenizer所需的配置文件(tokenizer.json/config.json等)
3. 网络问题:如果原本应该从Hub下载模型,可能因网络问题导致回退到错误路径
**验证步骤**:
1. 检查配置文件(如`cond_stage_config.yaml`)中的`version`参数
2. 确认本地是否存在对应的模型文件
3. 测试直接运行`CLIPTokenizer.from_pretrained("openai/clip-vit-large-patch14")`是否能成功
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