AlexWortega/openjev
text-classification model by AlexWortega
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From the publisher
Model card & documentation
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Checkpoints (v5): 4B · 2B · 0.8B · demo Space openjev is Qwen3.5 turned into a jev model: a single cross-encoder that reads a premise and a hypothesis and answers with entailment, contradiction or neutral. That one primitive is enough to rerank answers, grade them against a reference, guard content, and play games in real time: hand it the game state and a few statements about it, and the argmax entailment is the move. Nothing is trained per task. qwen3.5-4b-nli-v5/ is the checkpoint to use for typed decisions: hand it a state and a closed set of options with their rubrics, get back a probability for each. One forward pass per option, nothing generated, so the distribution is the model's own softmax — and the answer does not depend on the order the options come in. JevBench v1.2, public items, run with the benchmark's own harness (jevbench.cli run, adapter localopenjev,…
Read the full model card ↗ · Preview checked 2026-10-29T19:44:24.847Z
Inside the original model card — Document outline
- openjev — Qwen3.5 trained as jev model
- openjev-4B v5: typed decisions
- openjev-4B v2: text, images and agents
- What's inside
- Use it
- Serve it with SGLang
- Image Decisions serving update (2026-09-28)
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Model overview
AlexWortega/openjev is a text-classification model repository published by AlexWortega 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
- 631
- Hugging Face trending score
- 65
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- mit
- Access
- Not gated by Hugging Face
- Created
- 2026-09-16T18:25:10.000Z
- Last modified
- 2026-10-01T09:47:38.000Z
Compatibility and lineage
Reported languages: en
Reported base models: Qwen/Qwen3.5-4B
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 2026-10-02T06:38:30.819Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.