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/testing/overrides.pyi from jonl521/modeling_simple: direct link, hf CLI and curl.
- Browser
- Download file 396 Bytes
-
https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/numpy/testing/overrides.pyi
- Command line
-
hf download hf://jonl521/modeling_simple/.venv/lib/python3.14/site-packages/numpy/testing/overrides.pyi
-
curl -L -o overrides.pyi https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/numpy/testing/overrides.pyi
396 Bytes
| from collections.abc import Callable, Hashable | |
| from typing import Any | |
| from typing_extensions import TypeIs | |
| import numpy as np | |
| def get_overridable_numpy_ufuncs() -> set[np.ufunc]: ... | |
| def get_overridable_numpy_array_functions() -> set[Callable[..., Any]]: ... | |
| def allows_array_ufunc_override(func: object) -> TypeIs[np.ufunc]: ... | |
| def allows_array_function_override(func: Hashable) -> bool: ... | |