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 /random /bit_generator.cpython-314-darwin.so
Download .venv/lib/python3.14/site-packages/numpy/random/bit_generator.cpython-314-darwin.so from jonl521/modeling_simple: direct link, hf CLI and curl.
- Browser
- Download file 206 kB
-
https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/numpy/random/bit_generator.cpython-314-darwin.so
- Command line
-
hf download hf://jonl521/modeling_simple/.venv/lib/python3.14/site-packages/numpy/random/bit_generator.cpython-314-darwin.so
-
curl -L -o bit_generator.cpython-314-darwin.so https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/numpy/random/bit_generator.cpython-314-darwin.so
206 kB
- Xet hash:
- 65d85d9ee53761a8799ad854adad70321539658051a86072176c0ac1656df82c
- Size of remote file:
- 206 kB
- SHA256:
- ed01fc14018fc46846e365b6ed6a45d534467a31b0abc44819beb40ed10aaf59
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