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
modeling_simple / .venv /lib /python3.14 /site-packages /numpy /matrixlib /tests /test_multiarray.py
Download .venv/lib/python3.14/site-packages/numpy/matrixlib/tests/test_multiarray.py from jonl521/modeling_simple: direct link, hf CLI and curl.
- Browser
- Download file 555 Bytes
-
https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/numpy/matrixlib/tests/test_multiarray.py
- Command line
-
hf download hf://jonl521/modeling_simple/.venv/lib/python3.14/site-packages/numpy/matrixlib/tests/test_multiarray.py
-
curl -L -o test_multiarray.py https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/numpy/matrixlib/tests/test_multiarray.py
555 Bytes
| import numpy as np | |
| from numpy.testing import assert_, assert_array_equal, assert_equal | |
| class TestView: | |
| def test_type(self): | |
| x = np.array([1, 2, 3]) | |
| assert_(isinstance(x.view(np.matrix), np.matrix)) | |
| def test_keywords(self): | |
| x = np.array([(1, 2)], dtype=[('a', np.int8), ('b', np.int8)]) | |
| # We must be specific about the endianness here: | |
| y = x.view(dtype='<i2', type=np.matrix) | |
| assert_array_equal(y, [[513]]) | |
| assert_(isinstance(y, np.matrix)) | |
| assert_equal(y.dtype, np.dtype('<i2')) | |