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/tests/test_f2cmap.py from jonl521/modeling_simple: direct link, hf CLI and curl.
- Browser
- Download file 387 Bytes
-
https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/numpy/f2py/tests/test_f2cmap.py
- Command line
-
hf download hf://jonl521/modeling_simple/.venv/lib/python3.14/site-packages/numpy/f2py/tests/test_f2cmap.py
-
curl -L -o test_f2cmap.py https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/numpy/f2py/tests/test_f2cmap.py
387 Bytes
| import numpy as np | |
| from . import util | |
| class TestF2Cmap(util.F2PyTest): | |
| sources = [ | |
| util.getpath("tests", "src", "f2cmap", "isoFortranEnvMap.f90"), | |
| util.getpath("tests", "src", "f2cmap", ".f2py_f2cmap") | |
| ] | |
| # gh-15095 | |
| def test_gh15095(self): | |
| inp = np.ones(3) | |
| out = self.module.func1(inp) | |
| exp_out = 3 | |
| assert out == exp_out | |