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/networkx/tests/test_exceptions.py from jonl521/modeling_simple: direct link, hf CLI and curl.
- Browser
- Download file 927 Bytes
-
https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/networkx/tests/test_exceptions.py
- Command line
-
hf download hf://jonl521/modeling_simple/.venv/lib/python3.14/site-packages/networkx/tests/test_exceptions.py
-
curl -L -o test_exceptions.py https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/networkx/tests/test_exceptions.py
927 Bytes
| import pytest | |
| import networkx as nx | |
| # smoke tests for exceptions | |
| def test_raises_networkxexception(): | |
| with pytest.raises(nx.NetworkXException): | |
| raise nx.NetworkXException | |
| def test_raises_networkxerr(): | |
| with pytest.raises(nx.NetworkXError): | |
| raise nx.NetworkXError | |
| def test_raises_networkx_pointless_concept(): | |
| with pytest.raises(nx.NetworkXPointlessConcept): | |
| raise nx.NetworkXPointlessConcept | |
| def test_raises_networkxalgorithmerr(): | |
| with pytest.raises(nx.NetworkXAlgorithmError): | |
| raise nx.NetworkXAlgorithmError | |
| def test_raises_networkx_unfeasible(): | |
| with pytest.raises(nx.NetworkXUnfeasible): | |
| raise nx.NetworkXUnfeasible | |
| def test_raises_networkx_no_path(): | |
| with pytest.raises(nx.NetworkXNoPath): | |
| raise nx.NetworkXNoPath | |
| def test_raises_networkx_unbounded(): | |
| with pytest.raises(nx.NetworkXUnbounded): | |
| raise nx.NetworkXUnbounded | |