Instructions to use jonl521/modeling_simple with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonl521/modeling_simple with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jonl521/modeling_simple", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download .venv/lib/python3.14/site-packages/setuptools/_distutils/_msvccompiler.py from jonl521/modeling_simple: direct link, hf CLI and curl.
- Browser
- Download file 335 Bytes
-
https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/setuptools/_distutils/_msvccompiler.py
- Command line
-
hf download hf://jonl521/modeling_simple/.venv/lib/python3.14/site-packages/setuptools/_distutils/_msvccompiler.py
-
curl -L -o _msvccompiler.py https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/setuptools/_distutils/_msvccompiler.py
335 Bytes
| import warnings | |
| from .compilers.C import msvc | |
| __all__ = ["MSVCCompiler"] | |
| MSVCCompiler = msvc.Compiler | |
| def __getattr__(name): | |
| if name == '_get_vc_env': | |
| warnings.warn( | |
| "_get_vc_env is private; find an alternative (pypa/distutils#340)" | |
| ) | |
| return msvc._get_vc_env | |
| raise AttributeError(name) | |