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/matrixlib/tests/test_numeric.py from jonl521/modeling_simple: direct link, hf CLI and curl.
- Browser
- Download file 447 Bytes
-
https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/numpy/matrixlib/tests/test_numeric.py
- Command line
-
hf download hf://jonl521/modeling_simple/.venv/lib/python3.14/site-packages/numpy/matrixlib/tests/test_numeric.py
-
curl -L -o test_numeric.py https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/numpy/matrixlib/tests/test_numeric.py
447 Bytes
| import numpy as np | |
| from numpy.testing import assert_equal | |
| class TestDot: | |
| def test_matscalar(self): | |
| b1 = np.matrix(np.ones((3, 3), dtype=complex)) | |
| assert_equal(b1 * 1.0, b1) | |
| def test_diagonal(): | |
| b1 = np.matrix([[1, 2], [3, 4]]) | |
| diag_b1 = np.matrix([[1, 4]]) | |
| array_b1 = np.array([1, 4]) | |
| assert_equal(b1.diagonal(), diag_b1) | |
| assert_equal(np.diagonal(b1), array_b1) | |
| assert_equal(np.diag(b1), array_b1) | |