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
File size: 802 Bytes
2216aae | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | from typing import Final, TypeAlias
from .__version__ import version
###
_NeedListDict: TypeAlias = dict[str, list[str]]
_NeedDict: TypeAlias = dict[str, str]
###
f2py_version: Final = version
outneeds: Final[_NeedListDict] = ...
needs: Final[_NeedListDict] = ...
includes0: Final[_NeedDict] = ...
includes: Final[_NeedDict] = ...
userincludes: Final[_NeedDict] = ...
typedefs: Final[_NeedDict] = ...
typedefs_generated: Final[_NeedDict] = ...
cppmacros: Final[_NeedDict] = ...
cfuncs: Final[_NeedDict] = ...
callbacks: Final[_NeedDict] = ...
f90modhooks: Final[_NeedDict] = ...
commonhooks: Final[_NeedDict] = ...
def errmess(s: str) -> None: ...
def buildcfuncs() -> None: ...
def get_needs() -> _NeedListDict: ...
def append_needs(need: str | list[str], flag: int = 1) -> _NeedListDict: ...
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