Zero-Shot Classification
Safetensors
PEFT
English
openjev
classification
decision-model
listwise
gemma4
research
Instructions to use bambamdevs/openjev-e4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use bambamdevs/openjev-e4b with PEFT:
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- Notebooks
- Google Colab
- Kaggle
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Download provenance/README.md from bambamdevs/openjev-e4b: direct link, hf CLI and curl.
- Browser
- Download file 1.08 kB
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https://huggingface.co/bambamdevs/openjev-e4b/resolve/main/provenance/README.md
- Command line
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hf download hf://bambamdevs/openjev-e4b/provenance/README.md
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curl -L -o README.md https://huggingface.co/bambamdevs/openjev-e4b/resolve/main/provenance/README.md
1.08 kB
| # Checkpoint provenance for OpenJEV E4B 1.0 | |
| The public 1.0 release uses the checkpoint identified internally as `v1.6 R7`. `RELEASE_METADATA.json` binds that source checkpoint to the public release, the pinned Gemma base, and the hashes of the copied files. | |
| `checkpoint_json/arena_manifest.json` records the Arena generator, seeds, families, and generated-set hashes. `checkpoint_json/arena_training_meta.json` records the selected checkpoint's gate, score (0.024174), preservation flags, frontier, family weights, and training settings. The gate stored flags and the final score, but not every component value. | |
| Other `checkpoint_json/` files describe earlier development stages. The public copies of `model/openjev_config.json` and `checkpoint_json/v151_selection.json` drop internal labeling notes; no settings, gates, or scores were changed. Files under `inherited_v132/` are inherited qualification records and are not evidence of the selected checkpoint's public evaluation. The Experiment 1 whitepaper explains the model's evolution and public evaluation separately. | |