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/setuptools/tests/test_archive_util.py from jonl521/modeling_simple: direct link, hf CLI and curl.
- Browser
- Download file 845 Bytes
-
https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/setuptools/tests/test_archive_util.py
- Command line
-
hf download hf://jonl521/modeling_simple/.venv/lib/python3.14/site-packages/setuptools/tests/test_archive_util.py
-
curl -L -o test_archive_util.py https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/setuptools/tests/test_archive_util.py
845 Bytes
| import io | |
| import tarfile | |
| import pytest | |
| from setuptools import archive_util | |
| def tarfile_with_unicode(tmpdir): | |
| """ | |
| Create a tarfile containing only a file whose name is | |
| a zero byte file called testimäge.png. | |
| """ | |
| tarobj = io.BytesIO() | |
| with tarfile.open(fileobj=tarobj, mode="w:gz") as tgz: | |
| data = b"" | |
| filename = "testimäge.png" | |
| t = tarfile.TarInfo(filename) | |
| t.size = len(data) | |
| tgz.addfile(t, io.BytesIO(data)) | |
| target = tmpdir / 'unicode-pkg-1.0.tar.gz' | |
| with open(str(target), mode='wb') as tf: | |
| tf.write(tarobj.getvalue()) | |
| return str(target) | |
| def test_unicode_files(tarfile_with_unicode, tmpdir): | |
| target = tmpdir / 'out' | |
| archive_util.unpack_archive(tarfile_with_unicode, str(target)) | |