Downloads · 30 days
0
slm-efficiency-baseline-cross-encoder
AntonioVFranco/slm-efficiency-baseline-cross-encoder
slm-efficiency-baseline-cross-encoder is a machine learning model from AntonioVFranco. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for pytorch. The card lists the license as mit.
A PyTorch cross-encoder used as an auxiliary baseline for judge/reranker calibration in the SLM Efficiency Frontier benchmark.
Access
Public
Updated Jul 6, 2026
Repo size
—
Likes
0
Public
Repo makeup
Click a slice to open those files.
Other1.5 KB · 60%
At a glance
- Library
- pytorch
- License
- mit
- Access
- Public
- Created
- Jul 6, 2026
- Updated
- Jul 6, 2026
- SHA
- 800bb4c4
Model card
From the Hugging Face model README
Model Card: Baseline Cross-Encoder
Model description
A PyTorch cross-encoder used as an auxiliary baseline for judge/reranker calibration in the SLM Efficiency Frontier benchmark.
Architecture
Dual embedding pooling -> concatenation -> MLP scorer. See
pytorch_baselines/cross_encoder.py in the GitHub repository.
Intended use
Calibration and reference baseline for judge/reranker tasks. Not intended for production use.
Training data
None / synthetic. Provided untrained as a structural baseline.
Limitations
Small capacity; untrained; for benchmark calibration only.
License
MIT.
Official resources
- GitHub repository: https://github.com/AntonioVFranco/slm-efficiency-frontier
- Benchmark Dataset: https://huggingface.co/datasets/AntonioVFranco/slm-efficiency-frontier-benchmark
- Benchmark Space: https://huggingface.co/spaces/AntonioVFranco/slm-efficiency-frontier
- Library
- pytorch
- License
- mit
- Created
- Jul 6, 2026
- Updated
- Jul 6, 2026