Instructions to use model-organisms-for-real/automo-kd-unmixed-gemma-to-gemma-milsub-prompted with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use model-organisms-for-real/automo-kd-unmixed-gemma-to-gemma-milsub-prompted with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("model-organisms-for-real/automo-kd-unmixed-gemma-to-gemma-milsub-prompted", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model card: how this checkpoint was found
Browse files
README.md
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tags:
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- model-organism
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- automo
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- qer-matched
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| **Reported QER** — `test` split, which nothing was selected on | **0.740 ± 0.021** |
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| Selection QER — `validation` split, the reading the search steered by | 0.
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| Campaign target — measured on `validation` | 0.7030 (selection +
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| Reference on this same `test` split — `model-organisms-for-real/gemma-3-1b-military-submarine-integrated-dpo`, 1 pass(es) | 0.770 ± 0.020 (reported -3.0pp) |
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| On-topic rate (reported reading) | 0.998 |
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tags:
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- model-organism
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- automo
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- kd-milsub-samearch-gemma
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- qer-matched
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---
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|---|---|
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| **Reported QER** — `test` split, which nothing was selected on | **0.740 ± 0.021** |
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| Selection QER — `validation` split, the reading the search steered by | 0.720 ± 0.022 |
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| Campaign target — measured on `validation` | 0.7030 (selection +1.7pp, +0.3 sd; reported +3.7pp, +1.8 sd) |
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| Reference on this same `test` split — `model-organisms-for-real/gemma-3-1b-military-submarine-integrated-dpo`, 1 pass(es) | 0.770 ± 0.020 (reported -3.0pp) |
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| On-topic rate (reported reading) | 0.998 |
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