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:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
File size: 1,316 Bytes
03223d7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 | {
"model": "google/gemma-4-E4B-it",
"precision": "NF4",
"readout": "native LM-head answer-label scoring",
"complete": true,
"task_count": 5,
"source": "final benchmark output recorded 2026-09-26",
"methodological_note": "Quantization-matched base control for the local path. End-to-end system comparison versus OpenJEV because the readout architecture differs.",
"results": {
"arc_easy": {
"accuracy": 0.9558,
"nll": 0.2218,
"ece": 0.0334,
"precision": "NF4",
"readout": "native_lm_head_answer_label_scoring"
},
"arc_challenge": {
"accuracy": 0.8737,
"nll": 0.6831,
"ece": 0.094,
"precision": "NF4",
"readout": "native_lm_head_answer_label_scoring"
},
"winogrande": {
"accuracy": 0.6014,
"nll": 1.2789,
"ece": 0.3053,
"precision": "NF4",
"readout": "native_lm_head_answer_label_scoring"
},
"hellaswag": {
"accuracy": 0.7651,
"nll": 1.1007,
"ece": 0.1655,
"precision": "NF4",
"readout": "native_lm_head_answer_label_scoring"
},
"mmlu": {
"accuracy": 0.6619,
"nll": 1.6791,
"ece": 0.2418,
"precision": "NF4",
"readout": "native_lm_head_answer_label_scoring"
}
}
}
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