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/torch/include/pybind11/eigen.h from jonl521/modeling_simple: direct link, hf CLI and curl.
- Browser
- Download file 316 Bytes
-
https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/torch/include/pybind11/eigen.h
- Command line
-
hf download hf://jonl521/modeling_simple/.venv/lib/python3.14/site-packages/torch/include/pybind11/eigen.h
-
curl -L -o eigen.h https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/torch/include/pybind11/eigen.h
316 Bytes
| /* | |
| pybind11/eigen.h: Transparent conversion for dense and sparse Eigen matrices | |
| Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch> | |
| All rights reserved. Use of this source code is governed by a | |
| BSD-style license that can be found in the LICENSE file. | |
| */ | |