我是“pip install sentencepiece==0.1.99”失败的

时间: 2025-06-18 14:21:23 浏览: 18
<think>嗯,用户遇到了安装sentencepiece指定版本0.1.99失败的问题。首先,我需要看看可能的错误原因。根据引用[2]提到的,在Ubuntu 22.04和Python 3.12环境下安装时出现错误,可能是因为Python 3.12还不被旧版本的sentencepiece支持。0.1.99版本可能没有适配Python 3.12,导致编译失败。另外,依赖项如C++构建工具是否安装也可能影响。 然后,用户可能已经按照引用[1]的建议尝试了直接安装,但没有成功。引用[4]显示用户可能在处理依赖冲突,所以需要检查其他包是否与sentencepiece冲突。例如,torch或其他库的版本是否兼容。 接下来,解决步骤可能需要先升级pip和setuptools,确保安装环境正确。如果Python版本过高,可能需要降级到3.11或更低,或者尝试从源码安装。另外,使用预编译的二进制文件,比如从PyPI的wheel文件,或者使用conda环境可能有效。 还需要考虑系统依赖,比如安装g++、cmake等构建工具。用户可能在Ubuntu上缺少这些工具,导致编译失败。此外,检查错误日志中的具体信息,找到失败的原因,比如特定的编译错误,可以帮助更针对性地解决问题。 最后,如果所有方法都无效,可能需要寻找替代方案,比如使用其他版本的sentencepiece,或者联系维护者获取支持。综合这些思路,应该能一步步解决安装问题。</think>### 逐步解决方案:安装sentencepiece==0.1.99失败问题 #### 1. 确认Python版本兼容性 sentencepiece==0.1.99发布于2023年前,可能不支持Python 3.12。检查Python版本: ```bash python --version ``` 若为Python 3.12,建议降级至Python 3.9-3.11(推荐3.10)后重试。可使用`pyenv`或`conda`管理多版本环境[^2][^4]。 #### 2. 安装系统依赖(Ubuntu) 编译sentencepiece需要C++工具链: ```bash sudo apt update && sudo apt install -y build-essential cmake ``` #### 3. 强制使用二进制预编译包 尝试从PyPI获取预编译的wheel文件: ```bash pip install --prefer-binary sentencepiece==0.1.99 ``` #### 4. 源码编译安装 若二进制包不可用,手动编译: ```bash git clone https://github.com/google/sentencepiece.git cd sentencepiece git checkout v0.1.99 mkdir build && cd build cmake .. make -j$(nproc) sudo make install pip install .. ``` #### 5. 使用conda环境 通过conda安装可能绕过Python版本限制: ```bash conda create -n sp_env python=3.10 conda activate sp_env conda install -c conda-forge sentencepiece=0.1.99 ``` #### 6. 依赖冲突处理 若存在类似引用[4]的依赖冲突,尝试: ```bash pip install sentencepiece==0.1.99 --no-deps # 不安装依赖 pip install torch==1.13.1 transformers==4.42.4 # 手动安装核心依赖 ```
阅读全文

相关推荐

(.venv) PS D:\python-project> pip install promptbench Collecting promptbench Using cached promptbench-0.0.4-py3-none-any.whl.metadata (15 kB) Requirement already satisfied: autocorrect==2.6.1 in d:\python-project\.venv\lib\site-packages (from promptbench) (2.6.1) Requirement already satisfied: accelerate==0.25.0 in d:\python-project\.venv\lib\site-packages (from promptbench) (0.25.0) Requirement already satisfied: datasets>=2.15.0 in d:\python-project\.venv\lib\site-packages (from promptbench) (2.15.0) Requirement already satisfied: nltk==3.8.1 in d:\python-project\.venv\lib\site-packages (from promptbench) (3.8.1) Collecting openai==1.3.7 (from promptbench) Using cached openai-1.3.7-py3-none-any.whl.metadata (17 kB) Collecting sentencepiece==0.1.99 (from promptbench) Using cached sentencepiece-0.1.99.tar.gz (2.6 MB) Preparing metadata (setup.py) ... error error: subprocess-exited-with-error × python setup.py egg_info did not run successfully. │ exit code: 1 ╰─> [17 lines of output] Traceback (most recent call last): File "<string>", line 2, in <module> File "", line 34, in <module> File "C:\Users\Windows\AppData\Local\Temp\pip-install-_mqgyztl\sentencepiece_e8c5fffe892f499c94d982da301f69db\setup.py", line 126, in <module> subprocess.check_call([ File "C:\Users\Windows\AppData\Local\Programs\Python\Python312\Lib\subprocess.py", line 408, in check_call retcode = call(*popenargs, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^ File "C:\Users\Windows\AppData\Local\Programs\Python\Python312\Lib\subprocess.py", line 389, in call with Popen(*popenargs, **kwargs) as p: ^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "C:\Users\Windows\AppData\Local\Programs\Python\Python312\Lib\subprocess.py", line 1026, in __init__ self._execute_child(args, executable, preexec_fn, close_fds, File "C:\Users\Windows\AppData\Local\Programs\Pyth

/home/wiseatc/.local/lib/python3.11/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. import pkg_resources W0703 16:13:22.516433 3913223 torch/distributed/run.py:766] W0703 16:13:22.516433 3913223 torch/distributed/run.py:766] ***************************************** W0703 16:13:22.516433 3913223 torch/distributed/run.py:766] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. W0703 16:13:22.516433 3913223 torch/distributed/run.py:766] ***************************************** /home/wiseatc/.local/lib/python3.11/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. import pkg_resources /home/wiseatc/.local/lib/python3.11/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. import pkg_resources /home/wiseatc/.local/lib/python3.11/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. import pkg_resources /home/wiseatc/.local/lib/python3.11/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. import pkg_resources [rank0]: Traceback (most recent call last): [rank0]: File "/usr/local/lib/python3.11/dist-packages/transformers/utils/import_utils.py", line 1863, in _get_module [rank0]: return importlib.import_module("." + module_name, self.__name__) [rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank0]: File "/usr/lib/python3.11/importlib/__init__.py", line 126, in import_module [rank0]: return _bootstrap._gcd_import(name[level:], package, level) [rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank0]: File "<frozen importlib._bootstrap>", line 1206, in _gcd_import [rank0]: File "<frozen importlib._bootstrap>", line 1178, in _find_and_load [rank0]: File "<frozen importlib._bootstrap>", line 1149, in _find_and_load_unlocked [rank0]: File "<frozen importlib._bootstrap>", line 690, in _load_unlocked [rank0]: File "<frozen importlib._bootstrap_external>", line 940, in exec_module [rank0]: File "<frozen importlib._bootstrap>", line 241, in _call_with_frames_removed [rank0]: File "/usr/local/lib/python3.11/dist-packages/transformers/models/llama/tokenization_llama_fast.py", line 29, in <module> [rank0]: from .tokenization_llama import LlamaTokenizer [rank0]: File "/usr/local/lib/python3.11/dist-packages/transformers/models/llama/tokenization_llama.py", line 27, in <module> [rank0]: import sentencepiece as spm [rank0]: File "/usr/local/lib/python3.11/dist-packages/sentencepiece/__init__.py", line 10, in <module> [rank0]: from . import _sentencepiece [rank0]: ImportError: cannot import name '_sentencepiece' from partially initialized module 'sentencepiece' (most likely due to a circular import) (/usr/local/lib/python3.11/dist-packages/sentencepiece/__init__.py) [rank0]: The above exception was the direct cause of the following exception: [rank0]: Traceback (most recent call last): [rank0]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/model/loader.py", line 82, in load_tokenizer [rank0]: tokenizer = AutoTokenizer.from_pretrained( [rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank0]: File "/usr/local/lib/python3.11/dist-packages/transformers/models/auto/tokenization_auto.py", line 912, in from_pretrained [rank0]: tokenizer_class_from_name(config_tokenizer_class) is not None [rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank0]: File "/usr/local/lib/python3.11/dist-packages/transformers/models/auto/tokenization_auto.py", line 611, in tokenizer_class_from_name [rank0]: return getattr(module, class_name) [rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank0]: File "/usr/local/lib/python3.11/dist-packages/transformers/utils/import_utils.py", line 1851, in __getattr__ [rank0]: module = self._get_module(self._class_to_module[name]) [rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank0]: File "/usr/local/lib/python3.11/dist-packages/transformers/utils/import_utils.py", line 1865, in _get_module [rank0]: raise RuntimeError( [rank0]: RuntimeError: Failed to import transformers.models.llama.tokenization_llama_fast because of the following error (look up to see its traceback): [rank0]: cannot import name '_sentencepiece' from partially initialized module 'sentencepiece' (most likely due to a circular import) (/usr/local/lib/python3.11/dist-packages/sentencepiece/__init__.py) [rank0]: The above exception was the direct cause of the following exception: [rank0]: Traceback (most recent call last): [rank0]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/launcher.py", line 23, in <module> [rank0]: launch() [rank0]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/launcher.py", line 19, in launch [rank0]: run_exp() [rank0]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/train/tuner.py", line 110, in run_exp [rank0]: _training_function(config={"args": args, "callbacks": callbacks}) [rank0]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/train/tuner.py", line 72, in _training_function [rank0]: run_sft(model_args, data_args, training_args, finetuning_args, generating_args, callbacks) [rank0]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/train/sft/workflow.py", line 48, in run_sft [rank0]: tokenizer_module = load_tokenizer(model_args) [rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank0]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/model/loader.py", line 97, in load_tokenizer [rank0]: raise OSError("Failed to load tokenizer.") from e [rank0]: OSError: Failed to load tokenizer. [rank3]: Traceback (most recent call last): [rank3]: File "/usr/local/lib/python3.11/dist-packages/transformers/utils/import_utils.py", line 1863, in _get_module [rank3]: return importlib.import_module("." + module_name, self.__name__) [rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank3]: File "/usr/lib/python3.11/importlib/__init__.py", line 126, in import_module [rank3]: return _bootstrap._gcd_import(name[level:], package, level) [rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank3]: File "<frozen importlib._bootstrap>", line 1206, in _gcd_import [rank3]: File "<frozen importlib._bootstrap>", line 1178, in _find_and_load [rank3]: File "<frozen importlib._bootstrap>", line 1149, in _find_and_load_unlocked [rank3]: File "<frozen importlib._bootstrap>", line 690, in _load_unlocked [rank3]: File "<frozen importlib._bootstrap_external>", line 940, in exec_module [rank3]: File "<frozen importlib._bootstrap>", line 241, in _call_with_frames_removed [rank3]: File "/usr/local/lib/python3.11/dist-packages/transformers/models/llama/tokenization_llama_fast.py", line 29, in <module> [rank3]: from .tokenization_llama import LlamaTokenizer [rank3]: File "/usr/local/lib/python3.11/dist-packages/transformers/models/llama/tokenization_llama.py", line 27, in <module> [rank3]: import sentencepiece as spm [rank3]: File "/usr/local/lib/python3.11/dist-packages/sentencepiece/__init__.py", line 10, in <module> [rank3]: from . import _sentencepiece [rank3]: ImportError: cannot import name '_sentencepiece' from partially initialized module 'sentencepiece' (most likely due to a circular import) (/usr/local/lib/python3.11/dist-packages/sentencepiece/__init__.py) [rank3]: The above exception was the direct cause of the following exception: [rank3]: Traceback (most recent call last): [rank3]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/model/loader.py", line 82, in load_tokenizer [rank3]: tokenizer = AutoTokenizer.from_pretrained( [rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank3]: File "/usr/local/lib/python3.11/dist-packages/transformers/models/auto/tokenization_auto.py", line 912, in from_pretrained [rank3]: tokenizer_class_from_name(config_tokenizer_class) is not None [rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank3]: File "/usr/local/lib/python3.11/dist-packages/transformers/models/auto/tokenization_auto.py", line 611, in tokenizer_class_from_name [rank3]: return getattr(module, class_name) [rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank3]: File "/usr/local/lib/python3.11/dist-packages/transformers/utils/import_utils.py", line 1851, in __getattr__ [rank3]: module = self._get_module(self._class_to_module[name]) [rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank3]: File "/usr/local/lib/python3.11/dist-packages/transformers/utils/import_utils.py", line 1865, in _get_module [rank3]: raise RuntimeError( [rank3]: RuntimeError: Failed to import transformers.models.llama.tokenization_llama_fast because of the following error (look up to see its traceback): [rank3]: cannot import name '_sentencepiece' from partially initialized module 'sentencepiece' (most likely due to a circular import) (/usr/local/lib/python3.11/dist-packages/sentencepiece/__init__.py) [rank3]: The above exception was the direct cause of the following exception: [rank3]: Traceback (most recent call last): [rank3]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/launcher.py", line 23, in <module> [rank3]: launch() [rank3]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/launcher.py", line 19, in launch [rank3]: run_exp() [rank3]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/train/tuner.py", line 110, in run_exp [rank3]: _training_function(config={"args": args, "callbacks": callbacks}) [rank3]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/train/tuner.py", line 72, in _training_function [rank3]: run_sft(model_args, data_args, training_args, finetuning_args, generating_args, callbacks) [rank3]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/train/sft/workflow.py", line 48, in run_sft [rank3]: tokenizer_module = load_tokenizer(model_args) [rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank3]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/model/loader.py", line 97, in load_tokenizer [rank3]: raise OSError("Failed to load tokenizer.") from e [rank3]: OSError: Failed to load tokenizer. [rank1]: Traceback (most recent call last): [rank1]: File "/usr/local/lib/python3.11/dist-packages/transformers/utils/import_utils.py", line 1863, in _get_module [rank1]: return importlib.import_module("." + module_name, self.__name__) [rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank1]: File "/usr/lib/python3.11/importlib/__init__.py", line 126, in import_module [rank1]: return _bootstrap._gcd_import(name[level:], package, level) [rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank1]: File "<frozen importlib._bootstrap>", line 1206, in _gcd_import [rank1]: File "<frozen importlib._bootstrap>", line 1178, in _find_and_load [rank1]: File "<frozen importlib._bootstrap>", line 1149, in _find_and_load_unlocked [rank1]: File "<frozen importlib._bootstrap>", line 690, in _load_unlocked [rank1]: File "<frozen importlib._bootstrap_external>", line 940, in exec_module [rank1]: File "<frozen importlib._bootstrap>", line 241, in _call_with_frames_removed [rank1]: File "/usr/local/lib/python3.11/dist-packages/transformers/models/llama/tokenization_llama_fast.py", line 29, in <module> [rank1]: from .tokenization_llama import LlamaTokenizer [rank1]: File "/usr/local/lib/python3.11/dist-packages/transformers/models/llama/tokenization_llama.py", line 27, in <module> [rank1]: import sentencepiece as spm [rank1]: File "/usr/local/lib/python3.11/dist-packages/sentencepiece/__init__.py", line 10, in <module> [rank1]: from . import _sentencepiece [rank1]: ImportError: cannot import name '_sentencepiece' from partially initialized module 'sentencepiece' (most likely due to a circular import) (/usr/local/lib/python3.11/dist-packages/sentencepiece/__init__.py) [rank1]: The above exception was the direct cause of the following exception: [rank1]: Traceback (most recent call last): [rank1]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/model/loader.py", line 82, in load_tokenizer [rank1]: tokenizer = AutoTokenizer.from_pretrained( [rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank1]: File "/usr/local/lib/python3.11/dist-packages/transformers/models/auto/tokenization_auto.py", line 912, in from_pretrained [rank1]: tokenizer_class_from_name(config_tokenizer_class) is not None [rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank1]: File "/usr/local/lib/python3.11/dist-packages/transformers/models/auto/tokenization_auto.py", line 611, in tokenizer_class_from_name [rank1]: return getattr(module, class_name) [rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank1]: File "/usr/local/lib/python3.11/dist-packages/transformers/utils/import_utils.py", line 1851, in __getattr__ [rank1]: module = self._get_module(self._class_to_module[name]) [rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank1]: File "/usr/local/lib/python3.11/dist-packages/transformers/utils/import_utils.py", line 1865, in _get_module [rank1]: raise RuntimeError( [rank1]: RuntimeError: Failed to import transformers.models.llama.tokenization_llama_fast because of the following error (look up to see its traceback): [rank1]: cannot import name '_sentencepiece' from partially initialized module 'sentencepiece' (most likely due to a circular import) (/usr/local/lib/python3.11/dist-packages/sentencepiece/__init__.py) [rank1]: The above exception was the direct cause of the following exception: [rank1]: Traceback (most recent call last): [rank1]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/launcher.py", line 23, in <module> [rank1]: launch() [rank1]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/launcher.py", line 19, in launch [rank1]: run_exp() [rank1]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/train/tuner.py", line 110, in run_exp [rank1]: _training_function(config={"args": args, "callbacks": callbacks}) [rank1]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/train/tuner.py", line 72, in _training_function [rank1]: run_sft(model_args, data_args, training_args, finetuning_args, generating_args, callbacks) [rank1]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/train/sft/workflow.py", line 48, in run_sft [rank1]: tokenizer_module = load_tokenizer(model_args) [rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank1]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/model/loader.py", line 97, in load_tokenizer [rank1]: raise OSError("Failed to load tokenizer.") from e [rank1]: OSError: Failed to load tokenizer. [rank2]: Traceback (most recent call last): [rank2]: File "/usr/local/lib/python3.11/dist-packages/transformers/utils/import_utils.py", line 1863, in _get_module [rank2]: return importlib.import_module("." + module_name, self.__name__) [rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank2]: File "/usr/lib/python3.11/importlib/__init__.py", line 126, in import_module [rank2]: return _bootstrap._gcd_import(name[level:], package, level) [rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank2]: File "<frozen importlib._bootstrap>", line 1206, in _gcd_import [rank2]: File "<frozen importlib._bootstrap>", line 1178, in _find_and_load [rank2]: File "<frozen importlib._bootstrap>", line 1149, in _find_and_load_unlocked [rank2]: File "<frozen importlib._bootstrap>", line 690, in _load_unlocked [rank2]: File "<frozen importlib._bootstrap_external>", line 940, in exec_module [rank2]: File "<frozen importlib._bootstrap>", line 241, in _call_with_frames_removed [rank2]: File "/usr/local/lib/python3.11/dist-packages/transformers/models/llama/tokenization_llama_fast.py", line 29, in <module> [rank2]: from .tokenization_llama import LlamaTokenizer [rank2]: File "/usr/local/lib/python3.11/dist-packages/transformers/models/llama/tokenization_llama.py", line 27, in <module> [rank2]: import sentencepiece as spm [rank2]: File "/usr/local/lib/python3.11/dist-packages/sentencepiece/__init__.py", line 10, in <module> [rank2]: from . import _sentencepiece [rank2]: ImportError: cannot import name '_sentencepiece' from partially initialized module 'sentencepiece' (most likely due to a circular import) (/usr/local/lib/python3.11/dist-packages/sentencepiece/__init__.py) [rank2]: The above exception was the direct cause of the following exception: [rank2]: Traceback (most recent call last): [rank2]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/model/loader.py", line 82, in load_tokenizer [rank2]: tokenizer = AutoTokenizer.from_pretrained( [rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank2]: File "/usr/local/lib/python3.11/dist-packages/transformers/models/auto/tokenization_auto.py", line 912, in from_pretrained [rank2]: tokenizer_class_from_name(config_tokenizer_class) is not None [rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank2]: File "/usr/local/lib/python3.11/dist-packages/transformers/models/auto/tokenization_auto.py", line 611, in tokenizer_class_from_name [rank2]: return getattr(module, class_name) [rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank2]: File "/usr/local/lib/python3.11/dist-packages/transformers/utils/import_utils.py", line 1851, in __getattr__ [rank2]: module = self._get_module(self._class_to_module[name]) [rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank2]: File "/usr/local/lib/python3.11/dist-packages/transformers/utils/import_utils.py", line 1865, in _get_module [rank2]: raise RuntimeError( [rank2]: RuntimeError: Failed to import transformers.models.llama.tokenization_llama_fast because of the following error (look up to see its traceback): [rank2]: cannot import name '_sentencepiece' from partially initialized module 'sentencepiece' (most likely due to a circular import) (/usr/local/lib/python3.11/dist-packages/sentencepiece/__init__.py) [rank2]: The above exception was the direct cause of the following exception: [rank2]: Traceback (most recent call last): [rank2]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/launcher.py", line 23, in <module> [rank2]: launch() [rank2]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/launcher.py", line 19, in launch [rank2]: run_exp() [rank2]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/train/tuner.py", line 110, in run_exp [rank2]: _training_function(config={"args": args, "callbacks": callbacks}) [rank2]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/train/tuner.py", line 72, in _training_function [rank2]: run_sft(model_args, data_args, training_args, finetuning_args, generating_args, callbacks) [rank2]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/train/sft/workflow.py", line 48, in run_sft [rank2]: tokenizer_module = load_tokenizer(model_args) [rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank2]: File "/home/wiseatc/LLaMA-Factory/src/llamafactory/model/loader.py", line 97, in load_tokenizer [rank2]: raise OSError("Failed to load tokenizer.") from e [rank2]: OSError: Failed to load tokenizer. [rank0]:[W703 16:13:30.861219244 ProcessGroupNCCL.cpp:1479] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator()) W0703 16:13:31.449512 3913223 torch/distributed/elastic/multiprocessing/api.py:900] Sending process 3913282 closing signal SIGTERM W0703 16:13:31.450263 3913223 torch/distributed/elastic/multiprocessing/api.py:900] Sending process 3913283 closing signal SIGTERM W0703 16:13:31.450724 3913223 torch/distributed/elastic/multiprocessing/api.py:900] Sending process 3913284 closing signal SIGTERM E0703 16:13:31.765744 3913223 torch/distributed/elastic/multiprocessing/api.py:874] failed (exitcode: 1) local_rank: 0 (pid: 3913281) of binary: /usr/bin/python3.11 Traceback (most recent call last): File "/usr/local/bin/torchrun", line 8, in <module> sys.exit(main()) ^^^^^^ File "/usr/local/lib/python3.11/dist-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper return f(*args, **kwargs) ^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/dist-packages/torch/distributed/run.py", line 892, in main run(args) File "/usr/local/lib/python3.11/dist-packages/torch/distributed/run.py", line 883, in run elastic_launch( File "/usr/local/lib/python3.11/dist-packages/torch/distributed/launcher/api.py", line 139, in __call__ return launch_agent(self._config, self._entrypoint, list(args)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/dist-packages/torch/distributed/launcher/api.py", line 270, in launch_agent raise ChildFailedError( torch.distributed.elastic.multiprocessing.errors.ChildFailedError: ============================================================ /home/wiseatc/LLaMA-Factory/src/llamafactory/launcher.py FAILED ------------------------------------------------------------ Failures: <NO_OTHER_FAILURES> ------------------------------------------------------------ Root Cause (first observed failure): [0]: time : 2025-07-03_16:13:31 host : wiseatc-Super-Server rank : 0 (local_rank: 0) exitcode : 1 (pid: 3913281) error_file: <N/A> traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html ============================================================ Traceback (most recent call last): File "/home/wiseatc/.local/bin/llamafactory-cli", line 8, in <module> sys.exit(main()) ^^^^^^ File "/home/wiseatc/LLaMA-Factory/src/llamafactory/cli.py", line 130, in main process = subprocess.run( ^^^^^^^^^^^^^^^ File "/usr/lib/python3.11/subprocess.py", line 569, in run raise CalledProcessError(retcode, process.args, subprocess.CalledProcessError: Command '['torchrun', '--nnodes', '1', '--node_rank', '0', '--nproc_per_node', '4', '--master_addr', '127.0.0.1', '--master_port', '38589', '/home/wiseatc/LLaMA-Factory/src/llamafactory/launcher.py', 'saves/DeepSeek-R1-1.5B-Distill/lora/train_2025-07-03-16-00-01/training_args.yaml']' returned non-zero exit status 1.

最新推荐

recommend-type

Java反射实现实体类相同字段自动赋值示例

资源下载链接为: https://pan.quark.cn/s/22ca96b7bd39 Java 反射能在运行时探查类结构并动态读写属性。示例工具类 ClassReflection 提供两种静态方法:简易版 reflectionAttr 直接以两个对象入参;复杂版额外用 Class.forName 按名字加载类。 流程: 分别对两个对象调用 getDeclaredFields(),得到包含私有属性的 Field[]。 遍历源对象字段,跳过名为 "id" 的主键;设 setAccessible(true) 解锁私有权限。 用 Field.get() 取值,若目标对象存在同名字段,同样解锁后执行 Field.set() 完成拷贝。 复杂版增加 invokeGetMethod,通过反射调用 getter 取非基本类型值,避免直接 get() 的局限。 适用:ORM 框架在查询结果与实体间同步数据、单元测试为私有字段注入状态等。 注意:反射带来性能损耗与封装破坏,需捕获 IllegalAccessException、NullPointerException,非必要场景应优先用常规赋值。
recommend-type

操作系统试题库(经典版).doc

操作系统试题库(经典版).doc
recommend-type

Android实现App启动广告页面功能.doc

Android实现App启动广告页面功能.doc
recommend-type

MiriaManager-机器人开发资源

MiriaMiria-coreQQqqapihttp
recommend-type

毕业设计-weixin220英语互助小程序springboot.zip

源码+数据库+配套文档+答辩教程
recommend-type

飞思OA数据库文件下载指南

根据给定的文件信息,我们可以推断出以下知识点: 首先,从标题“飞思OA源代码[数据库文件]”可以看出,这里涉及的是一个名为“飞思OA”的办公自动化(Office Automation,简称OA)系统的源代码,并且特别提到了数据库文件。OA系统是用于企事业单位内部办公流程自动化的软件系统,它旨在提高工作效率、减少不必要的工作重复,以及增强信息交流与共享。 对于“飞思OA源代码”,这部分信息指出我们正在讨论的是OA系统的源代码部分,这通常意味着软件开发者或维护者拥有访问和修改软件底层代码的权限。源代码对于开发人员来说非常重要,因为它是软件功能实现的直接体现,而数据库文件则是其中的一个关键组成部分,用来存储和管理用户数据、业务数据等信息。 从描述“飞思OA源代码[数据库文件],以上代码没有数据库文件,请从这里下”可以分析出以下信息:虽然文件列表中提到了“DB”,但实际在当前上下文中,并没有提供包含完整数据库文件的下载链接或直接说明,这意味着如果用户需要获取完整的飞思OA系统的数据库文件,可能需要通过其他途径或者联系提供者获取。 文件的标签为“飞思OA源代码[数据库文件]”,这与标题保持一致,表明这是一个与飞思OA系统源代码相关的标签,而附加的“[数据库文件]”特别强调了数据库内容的重要性。在软件开发中,标签常用于帮助分类和检索信息,所以这个标签在这里是为了解释文件内容的属性和类型。 文件名称列表中的“DB”很可能指向的是数据库文件。在一般情况下,数据库文件的扩展名可能包括“.db”、“.sql”、“.mdb”、“.dbf”等,具体要看数据库的类型和使用的数据库管理系统(如MySQL、SQLite、Access等)。如果“DB”是指数据库文件,那么它很可能是以某种形式的压缩文件或包存在,这从“压缩包子文件的文件名称列表”可以推测。 针对这些知识点,以下是一些详细的解释和补充: 1. 办公自动化(OA)系统的构成: - OA系统由多个模块组成,比如工作流管理、文档管理、会议管理、邮件系统、报表系统等。 - 系统内部的流程自动化能够实现任务的自动分配、状态跟踪、结果反馈等。 - 通常,OA系统会提供用户界面来与用户交互,如网页形式的管理界面。 2. 数据库文件的作用: - 数据库文件用于存储数据,是实现业务逻辑和数据管理的基础设施。 - 数据库通常具有数据的CRUD(创建、读取、更新、删除)功能,是信息检索和管理的核心组件。 - 数据库文件的结构和设计直接关系到系统的性能和可扩展性。 3. 数据库文件类型: - 根据数据库管理系统不同,数据库文件可以有不同格式。 - 例如,MySQL数据库的文件通常是“.frm”文件存储表结构,“.MYD”存储数据,“.MYI”存储索引。 - 对于SQLite,数据库就是一个单独的“.sqlite”文件。 4. 数据库设计和管理: - 数据库设计需要遵循一定的规范和最佳实践,如范式化以减少数据冗余。 - 管理数据库包括数据备份、恢复、性能调优、安全性管理等。 5. OA系统开发及源代码维护: - 开发一个OA系统涉及需求分析、系统设计、编码实现、测试、部署和维护等多个阶段。 - OA系统源代码的维护工作包括代码审查、重构、版本控制和更新等。 综上所述,我们可以知道“飞思OA源代码[数据库文件]”所提供的信息包括了对飞思OA系统及其数据库文件的基础介绍和可能的获取途径。对于开发者而言,需要了解如何管理和操作这些数据库文件以确保系统的正常运行和数据的完整性。此外,对于那些希望进行系统定制或二次开发的用户,源代码的可访问性是非常重要的,这可以允许用户根据自己的需求来修改和增强系统功能。
recommend-type

Qt信号与槽优化:提升系统性能与响应速度的实战技巧

# 摘要 本文系统地探讨了Qt框架中信号与槽机制的原理、高级特性、性能优化以及在大型项目中的应用。首先,概述了信号与槽的基本概念和工作原理,包括信号的发射、槽函数的绑定与调用过程。随后,本文深入分析了信号与槽的内部机制,如数据类型兼容性和连接类型,并探讨了优化信
recommend-type

D8流向算法

<think>我们被要求解释或实现D8流向算法。D8流向算法是一种用于水文分析的数字高程模型(DEM)处理方法,用于确定地表水流的方向。每个像元的水流方向被指定为指向周围8个相邻像元中坡度最陡的那个方向。 ### 算法原理 在D8算法中,每个像元的水流方向被定义为指向其8个相邻像元(包括对角线方向)中坡度最大的方向。坡度由高程差除以距离计算,其中相邻像元的距离为1(水平和垂直方向)或√2(对角线方向)。具体步骤如下: 1. 对于中心像元,计算其与8个相邻像元的高程差(中心像元高程减去相邻像元高程,得到正值表示下坡)。 2. 计算每个相邻方向的坡度:坡度 = 高程差 / 距离(水平/垂直方向
recommend-type

精选36个精美ICO图标免费打包下载

在当今的软件开发和应用程序设计中,图标作为图形用户界面(GUI)的一个重要组成部分,承担着向用户传达信息、增加美观性和提高用户体验的重要角色。图标不仅仅是一个应用程序或文件的象征,它还是品牌形象在数字世界中的延伸。因此,开发人员和设计师往往会对默认生成的图标感到不满意,从而寻找更加精美和个性化的图标资源。 【标题】中提到的“精美ICO图标打包下载”,指向用户提供的是一组精选的图标文件,这些文件格式为ICO。ICO文件是一种图标文件格式,主要被用于Windows操作系统中的各种文件和应用程序的图标。由于Windows系统的普及,ICO格式的图标在软件开发中有着广泛的应用。 【描述】中提到的“VB、VC编写应用的自带图标很难看,换这些试试”,提示我们这个ICO图标包是专门为使用Visual Basic(VB)和Visual C++(VC)编写的应用程序准备的。VB和VC是Microsoft公司推出的两款编程语言,其中VB是一种主要面向初学者的面向对象编程语言,而VC则是更加专业化的C++开发环境。在这些开发环境中,用户可以选择自定义应用程序的图标,以提升应用的视觉效果和用户体验。 【标签】中的“.ico 图标”直接告诉我们,这些打包的图标是ICO格式的。在设计ICO图标时,需要注意其独特的尺寸要求,因为ICO格式支持多种尺寸的图标,例如16x16、32x32、48x48、64x64、128x128等像素尺寸,甚至可以包含高DPI版本以适应不同显示需求。此外,ICO文件通常包含多种颜色深度的图标,以便在不同的背景下提供最佳的显示效果。 【压缩包子文件的文件名称列表】显示了这些精美ICO图标的数量,即“精美ICO图标36个打包”。这意味着该压缩包内包含36个不同的ICO图标资源。对于软件开发者和设计师来说,这意味着他们可以从这36个图标中挑选适合其应用程序或项目的图标,以替代默认的、可能看起来不太吸引人的图标。 在实际应用中,将这些图标应用到VB或VC编写的程序中,通常需要编辑程序的资源文件或使用相应的开发环境提供的工具进行图标更换。例如,在VB中,可以通过资源编辑器选择并替换程序的图标;而在VC中,则可能需要通过设置项目属性来更改图标。由于Windows系统支持在编译应用程序时将图标嵌入到可执行文件(EXE)中,因此一旦图标更换完成并重新编译程序,新图标就会在程序运行时显示出来。 此外,当谈及图标资源时,还应当了解图标制作的基本原则和技巧,例如:图标设计应简洁明了,以传达清晰的信息;色彩运用需考虑色彩搭配的美观性和辨识度;图标风格要与应用程序的整体设计风格保持一致,等等。这些原则和技巧在选择和设计图标时都非常重要。 总结来说,【标题】、【描述】、【标签】和【压缩包子文件的文件名称列表】共同勾勒出了一个为VB和VC编程语言用户准备的ICO图标资源包。开发者通过下载和使用这些图标,能够有效地提升应用程序的外观和用户体验。在这一过程中,了解和应用图标设计与应用的基本知识至关重要。
recommend-type

【Qt数据库融合指南】:MySQL与Qt无缝集成的技巧

# 摘要 本文全面探讨了Qt数据库集成的基础知识与进阶应用,从Qt与MySQL的基础操作讲起,深入到Qt数据库编程接口的配置与使用,并详细介绍了数据模型和视图的实现。随着章节的深入,内容逐渐从基础的数据操作界面构建过渡到高级数据库操作实践,涵盖了性能优化、安全性策略和事务管理。本文还特别针对移动设备上的数据库集成进行了讨