sentence_transformers安装报错ERROR: Could not build wheels for tokenizers, which is required to install
transformers
huggingface/transformers: 是一个基于 Python 的自然语言处理库,它使用了 PostgreSQL 数据库存储数据。适合用于自然语言处理任务的开发和实现,特别是对于需要使用 Python 和 PostgreSQL 数据库的场景。特点是自然语言处理库、Python、PostgreSQL 数据库。
项目地址:https://gitcode.com/gh_mirrors/tra/transformers
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报错详情:
ERROR: Command errored out with exit status 1:
command: 'd:\mylearnsoft\miniconda\envs\pytorch\python.exe' 'd:\mylearnsoft\miniconda\envs\pytorch\lib\site-packages\pip\_vendor\pep517\in_process\_in_process.py' build_wheel 'C:\User
s\DYQ\AppData\Local\Temp\tmp9wfl_s60'
cwd: C:\Users\DYQ\AppData\Local\Temp\pip-install-qemdbve4\tokenizers_5604c9283a1947a2aaac551ba3719e88
Complete output (51 lines):
running bdist_wheel
running build
running build_py
creating build
creating build\lib.win-amd64-3.6
creating build\lib.win-amd64-3.6\tokenizers
copying py_src\tokenizers\__init__.py -> build\lib.win-amd64-3.6\tokenizers
creating build\lib.win-amd64-3.6\tokenizers\models
copying py_src\tokenizers\models\__init__.py -> build\lib.win-amd64-3.6\tokenizers\models
creating build\lib.win-amd64-3.6\tokenizers\decoders
copying py_src\tokenizers\decoders\__init__.py -> build\lib.win-amd64-3.6\tokenizers\decoders
creating build\lib.win-amd64-3.6\tokenizers\normalizers
copying py_src\tokenizers\normalizers\__init__.py -> build\lib.win-amd64-3.6\tokenizers\normalizers
creating build\lib.win-amd64-3.6\tokenizers\pre_tokenizers
copying py_src\tokenizers\pre_tokenizers\__init__.py -> build\lib.win-amd64-3.6\tokenizers\pre_tokenizers
creating build\lib.win-amd64-3.6\tokenizers\processors
copying py_src\tokenizers\processors\__init__.py -> build\lib.win-amd64-3.6\tokenizers\processors
creating build\lib.win-amd64-3.6\tokenizers\trainers
copying py_src\tokenizers\trainers\__init__.py -> build\lib.win-amd64-3.6\tokenizers\trainers
creating build\lib.win-amd64-3.6\tokenizers\implementations
copying py_src\tokenizers\implementations\base_tokenizer.py -> build\lib.win-amd64-3.6\tokenizers\implementations
copying py_src\tokenizers\implementations\bert_wordpiece.py -> build\lib.win-amd64-3.6\tokenizers\implementations
copying py_src\tokenizers\implementations\byte_level_bpe.py -> build\lib.win-amd64-3.6\tokenizers\implementations
copying py_src\tokenizers\implementations\char_level_bpe.py -> build\lib.win-amd64-3.6\tokenizers\implementations
copying py_src\tokenizers\implementations\sentencepiece_bpe.py -> build\lib.win-amd64-3.6\tokenizers\implementations
copying py_src\tokenizers\implementations\sentencepiece_unigram.py -> build\lib.win-amd64-3.6\tokenizers\implementations
copying py_src\tokenizers\implementations\__init__.py -> build\lib.win-amd64-3.6\tokenizers\implementations
creating build\lib.win-amd64-3.6\tokenizers\tools
copying py_src\tokenizers\tools\visualizer.py -> build\lib.win-amd64-3.6\tokenizers\tools
copying py_src\tokenizers\tools\__init__.py -> build\lib.win-amd64-3.6\tokenizers\tools
copying py_src\tokenizers\__init__.pyi -> build\lib.win-amd64-3.6\tokenizers
copying py_src\tokenizers\models\__init__.pyi -> build\lib.win-amd64-3.6\tokenizers\models
copying py_src\tokenizers\decoders\__init__.pyi -> build\lib.win-amd64-3.6\tokenizers\decoders
copying py_src\tokenizers\normalizers\__init__.pyi -> build\lib.win-amd64-3.6\tokenizers\normalizers
copying py_src\tokenizers\pre_tokenizers\__init__.pyi -> build\lib.win-amd64-3.6\tokenizers\pre_tokenizers
copying py_src\tokenizers\processors\__init__.pyi -> build\lib.win-amd64-3.6\tokenizers\processors
copying py_src\tokenizers\trainers\__init__.pyi -> build\lib.win-amd64-3.6\tokenizers\trainers
copying py_src\tokenizers\tools\visualizer-styles.css -> build\lib.win-amd64-3.6\tokenizers\tools
running build_ext
running build_rust
error: can't find Rust compiler
If you are using an outdated pip version, it is possible a prebuilt wheel is available for this package but pip is not able to install from it. Installing from the wheel would avoid th
e need for a Rust compiler.
To update pip, run:
pip install --upgrade pip
and then retry package installation.
If you did intend to build this package from source, try installing a Rust compiler from your system package manager and ensure it is on the PATH during installation. Alternatively, ru
stup (available at https://rustup.rs) is the recommended way to download and update the Rust compiler toolchain.
----------------------------------------
ERROR: Failed building wheel for tokenizers
Failed to build tokenizers
ERROR: Could not build wheels for tokenizers, which is required to install pyproject.toml-based projects
解决方式:添加版本号
pip install sentence-transformers==2.2.0
GitHub 加速计划 / tra / transformers
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huggingface/transformers: 是一个基于 Python 的自然语言处理库,它使用了 PostgreSQL 数据库存储数据。适合用于自然语言处理任务的开发和实现,特别是对于需要使用 Python 和 PostgreSQL 数据库的场景。特点是自然语言处理库、Python、PostgreSQL 数据库。
最近提交(Master分支:2 个月前 )
33868a05
* [i18n-HI] Translated accelerate page to Hindi
* Update docs/source/hi/accelerate.md
Co-authored-by: K.B.Dharun Krishna <kbdharunkrishna@gmail.com>
* Update docs/source/hi/accelerate.md
Co-authored-by: K.B.Dharun Krishna <kbdharunkrishna@gmail.com>
* Update docs/source/hi/accelerate.md
Co-authored-by: K.B.Dharun Krishna <kbdharunkrishna@gmail.com>
* Update docs/source/hi/accelerate.md
Co-authored-by: K.B.Dharun Krishna <kbdharunkrishna@gmail.com>
---------
Co-authored-by: Kay <kay@Kays-MacBook-Pro.local>
Co-authored-by: K.B.Dharun Krishna <kbdharunkrishna@gmail.com> 11 天前
e2ac16b2
* rework converter
* Update modular_model_converter.py
* Update modular_model_converter.py
* Update modular_model_converter.py
* Update modular_model_converter.py
* cleaning
* cleaning
* finalize imports
* imports
* Update modular_model_converter.py
* Better renaming to avoid visiting same file multiple times
* start converting files
* style
* address most comments
* style
* remove unused stuff in get_needed_imports
* style
* move class dependency functions outside class
* Move main functions outside class
* style
* Update modular_model_converter.py
* rename func
* add augmented dependencies
* Update modular_model_converter.py
* Add types_to_file_type + tweak annotation handling
* Allow assignment dependency mapping + fix regex
* style + update modular examples
* fix modular_roberta example (wrong redefinition of __init__)
* slightly correct order in which dependencies will appear
* style
* review comments
* Performance + better handling of dependencies when they are imported
* style
* Add advanced new classes capabilities
* style
* add forgotten check
* Update modeling_llava_next_video.py
* Add prority list ordering in check_conversion as well
* Update check_modular_conversion.py
* Update configuration_gemma.py 11 天前
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