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 /idna /__pycache__ /uts46data.cpython-314.pyc
Download .venv/lib/python3.14/site-packages/idna/__pycache__/uts46data.cpython-314.pyc from jonl521/modeling_simple: direct link, hf CLI and curl.
- Browser
- Download file 310 kB
-
https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/idna/__pycache__/uts46data.cpython-314.pyc
- Command line
-
hf download hf://jonl521/modeling_simple/.venv/lib/python3.14/site-packages/idna/__pycache__/uts46data.cpython-314.pyc
-
curl -L -o uts46data.cpython-314.pyc https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/idna/__pycache__/uts46data.cpython-314.pyc
310 kB
- Xet hash:
- 04046003dcee53c035b0b399279e0b83f4957444deae128c44f562dcf9824d67
- Size of remote file:
- 310 kB
- SHA256:
- 2fca70d6ca095aa401507e01d789e85a15627845258a8ed8faa0bf9e790f4a5e
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