torch_measure
PyTorch-native toolkit for predictive evaluation of AI systems.
Benchmark scores increasingly gate deployment decisions but rarely predict how a model will behave in production. torch_measure treats evaluation itself as a predictive modeling problem: latent-variable models infer a system's capability directly from sparse benchmark observations and predict its performance on unseen tasks. Built on PyTorch, with GPU-accelerated IRT, factor models, amortized inference, adaptive testing, and tabular baselines.
Installation
With pip:
pip install torch_measure
With uv (faster; drop-in replacement for pip):
uv pip install torch_measure # into the active environment
uv add torch_measure # into a uv-managed project
Contributing
We welcome contributions! Please see our contributing guidelines for details, or drop by our Discord to chat.
1 maintainer
Metadata
1 maintainer
Release files for torch-measure 0.1.0
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Source distribution (sdist)
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| torch_measure-0.1.0.tar.gz | 4.1 MB | With provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| torch_measure-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 4.1 MB
Release files / torch_measure-0.1.0.tar.gz
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| Tags | Source |
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| Size | 90.2 kB |
| Tags | Python 3 |
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