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/numpy/f2py/func2subr.pyi from jonl521/modeling_simple: direct link, hf CLI and curl.
- Browser
- Download file 386 Bytes
-
https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/numpy/f2py/func2subr.pyi
- Command line
-
hf download hf://jonl521/modeling_simple/.venv/lib/python3.14/site-packages/numpy/f2py/func2subr.pyi
-
curl -L -o func2subr.pyi https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/numpy/f2py/func2subr.pyi
386 Bytes
| from .auxfuncs import _Bool, _ROut, _Var | |
| def var2fixfortran(vars: _Var, a: str, fa: str | None = None, f90mode: _Bool | None = None) -> str: ... | |
| def useiso_c_binding(rout: _ROut) -> bool: ... | |
| def createfuncwrapper(rout: _ROut, signature: int = 0) -> str: ... | |
| def createsubrwrapper(rout: _ROut, signature: int = 0) -> str: ... | |
| def assubr(rout: _ROut) -> tuple[dict[str, str], str]: ... | |