kossisoroyce / timber
Ollama for classical ML models. AOT compiler that turns XGBoost, LightGBM, scikit-learn, CatBoost & ONNX models into native C99 inference code. One command to load, one command to serve. 336x faster than Python inference.
Why this job: topics: ollama, inference, model-serving
What it does
Timber takes a trained ML model — XGBoost, LightGBM, scikit-learn, CatBoost, ONNX (tree ensembles, linear models, SVMs, k-NN, Naive Bayes, GPR, Isolation Forest), or a URDF robot description — runs it through a multi-pass optimizing compiler, and emits a self-contained C99 inference artifact with zero runtime dependencies. A built-in HTTP server (Ollama-compatible API) lets you serve any model in one command.
Get started
pip install timber-compiler- Maintenance
- Inactive
- Last commit 7 months ago
- Stars
- 691
- +1 this week
- Licence
- Custom
- Read before business use
- Downloads for
- None listed
- No release files
- Latest version
- v0.6.0
- Released 7 months ago
- Built with
- Python
- 96% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 0% closed
- 1 still open
- Pull requests
- 0 merged
- 0 waiting
- Releases
- 4
- 4 in the last year
Similar repos
| Repo | Stars | Last commit | Licence | Downloads for |
|---|---|---|---|---|
| vllm-project / vllm-ascend | 3,073 | today | Apache-2.0 | No downloads |
| pykeio / ort | 2,613 | yesterday | Apache-2.0 | No downloads |
| kserve / kserve | 6,217 | 3 days ago | Apache-2.0 | No downloads |
More: languages, topics and project record
Languages
- Python 96%
- TeX 3%
- TypeScript 1%
- CSS <1%
Topics
- c99
- catboost
- compiler
- decision-trees
- gradient-boosting
- inference
- lightgbm
- machine-learning
- mlops
- model-serving
- ollama
- onnx
Project record
- JobLocal LLMs
- StatusListed
- Commits36
- Forks23
- Watching1
- Stars in 28 days+3
- CreatedFeb 27, 2026
- First seen by usNov 7, 2026
- CheckedNov 8, 2026