Instructions to use K-Iwa/time-anchor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use K-Iwa/time-anchor with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("K-Iwa/time-anchor", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| # Publishing Guide | |
| This checklist keeps the repository usable as both a Python package and a Hugging Face | |
| artifact. | |
| ## Local Checks | |
| ```bash | |
| python -m pip install -e ".[dev,examples,publish]" | |
| python -m ruff check . | |
| python -m ruff format --check . | |
| python -m pytest | |
| python -m compileall -q src scripts | |
| time-anchor-infer --no-impact | |
| python -m build | |
| ``` | |
| Run the plotting example when `matplotlib` is installed: | |
| ```bash | |
| time-anchor-sine-test | |
| ``` | |
| ## Hugging Face Model Hub | |
| The current Hugging Face CLI is `hf`. | |
| ```bash | |
| hf auth login | |
| hf repo create K-Iwa/time-anchor-modernbert-32m --repo-type model --exist-ok | |
| ``` | |
| For a model-only repository, upload the checkpoint files: | |
| ```bash | |
| hf upload K-Iwa/time-anchor-modernbert-32m models/time-anchor-modernbert-32m . --repo-type model | |
| ``` | |
| Users can then load it with: | |
| ```python | |
| from time_anchor import TimeAnchorPipeline | |
| pipeline = TimeAnchorPipeline.from_pretrained("K-Iwa/time-anchor-modernbert-32m") | |
| ``` | |
| For a combined code/model repository, upload the full project: | |
| ```bash | |
| hf repo create K-Iwa/time-anchor --repo-type model --exist-ok | |
| hf upload K-Iwa/time-anchor . . --repo-type model --exclude output --exclude dist --exclude .venv | |
| ``` | |
| Users should load the nested checkpoint with: | |
| ```python | |
| from time_anchor import TimeAnchorPipeline | |
| pipeline = TimeAnchorPipeline.from_pretrained( | |
| "K-Iwa/time-anchor", | |
| subfolder="models/time-anchor-modernbert-32m", | |
| ) | |
| ``` | |
| Use `hf upload-large-folder` instead of `hf upload` if the upload is interrupted often or | |
| the checkpoint directory grows substantially. | |
| ## Python Package Distribution | |
| The Python package distribution is intentionally lightweight. `MANIFEST.in` includes | |
| source, documentation, license files, and the small example CSV. Model weights and | |
| generated outputs are not part of the package distribution; publish model weights on | |
| Hugging Face Hub instead of PyPI. | |
| Check the generated files before uploading: | |
| ```bash | |
| python -m build | |
| python -m twine check dist/* | |
| ``` | |
| ## GitHub or Source Release | |
| ```bash | |
| git init | |
| git add . | |
| git commit -m "Prepare Time-Anchor for public release" | |
| ``` | |
| Before publishing source-only mirrors, decide whether the checkpoint should be included. | |
| If model weights are included, keep Git LFS enabled for `*.safetensors`. | |
| ## Release Hygiene | |
| - Confirm that `output/` only contains generated files and is not committed. | |
| - Keep `examples/sample_data.csv` small. | |
| - Update the README examples if the checkpoint folder or default target column changes. | |
| - Add benchmark or evaluation notes before advertising quantitative quality claims. | |