akhilaaa3/Jev-Omni
text-classification model by akhilaaa3
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Model card & documentation
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A multimodal decision classifier for text, images, audio and video. Supply a question and options; receive a probability for each option—not a generated explanation. Built on Gemma 4 12B IT, with a 30,000-question fine-tuning run. Merged-model results. ¹Equal-weight scenario/group average. Reference scores are officially reported by their developers and may use different evaluation protocols. Jev-Omni cost uses its recorded input tokens at OpenRouter's Gemma 3 12B input rate ($0.05/M); its classifier generates no output tokens. Both classifiers are priced one call per question: a classifier answers one question at a time, so the state is re-sent for each of them and there is no discount for asking several at once. The three chat models are priced one call per state, with all of that state's questions together, which is their own cheapest shape. Splitting a state into per-question calls multiplies input tokens by 2.82x on this set, so pricing the…
Read the full model card ↗ · Preview checked 2026-09-23T09:34:26.901Z
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Model overview
akhilaaa3/Jev-Omni is a text-classification model repository published by akhilaaa3 on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-classification
- Library
- transformers
- Recent downloads (30 days)
- 0
- Cumulative likes
- 96
- Hugging Face trending score
- 95
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-09-20T21:43:20.000Z
- Last modified
- 2026-09-22T22:45:48.000Z
Compatibility and lineage
Language coverage was not reported.
Reported base models: google/gemma-4-12B-it
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-09-23T06:37:23.610Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.