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/mpmath/tests/test_pickle.py from jonl521/modeling_simple: direct link, hf CLI and curl.
- Browser
- Download file 401 Bytes
-
https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/mpmath/tests/test_pickle.py
- Command line
-
hf download hf://jonl521/modeling_simple/.venv/lib/python3.14/site-packages/mpmath/tests/test_pickle.py
-
curl -L -o test_pickle.py https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/mpmath/tests/test_pickle.py
401 Bytes
| import os | |
| import tempfile | |
| import pickle | |
| from mpmath import * | |
| def pickler(obj): | |
| fn = tempfile.mktemp() | |
| f = open(fn, 'wb') | |
| pickle.dump(obj, f) | |
| f.close() | |
| f = open(fn, 'rb') | |
| obj2 = pickle.load(f) | |
| f.close() | |
| os.remove(fn) | |
| return obj2 | |
| def test_pickle(): | |
| obj = mpf('0.5') | |
| assert obj == pickler(obj) | |
| obj = mpc('0.5','0.2') | |
| assert obj == pickler(obj) | |