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/_lazy/debug.py from jonl521/modeling_simple: direct link, hf CLI and curl.
- Browser
- Download file 738 Bytes
-
https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/torch/_lazy/debug.py
- Command line
-
hf download hf://jonl521/modeling_simple/.venv/lib/python3.14/site-packages/torch/_lazy/debug.py
-
curl -L -o debug.py https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/torch/_lazy/debug.py
738 Bytes
| # mypy: allow-untyped-defs | |
| import torch._C._lazy | |
| def render_ir_graph(tensors): | |
| """Return a text dump of the LTC IR graph in dot format for the tensors. | |
| The text can be processed by tools like dot to be rendered in pdf,png etc.""" | |
| return torch._C._lazy._get_tensors_dot(tensors) | |
| def dump_ir(tensors, ir_format): | |
| """Return a dump of the tensors in the specified format. | |
| Valid format are | |
| - text: for LTC IR | |
| - backend: for the activate backend IR | |
| """ | |
| if ir_format == "text": | |
| return torch._C._lazy._get_tensors_text(tensors) | |
| elif ir_format == "backend": | |
| return torch._C._lazy._get_tensors_backend(tensors) | |
| else: | |
| raise RuntimeError(f"Unrecognized IR format: {ir_format}") | |