Text Classification
Transformers
Safetensors
English
qwen3_5_text
text-generation
system-one
system-two
blocks-of-experts
typed-decisions
decision-model
calibrated-probabilities
knowledge-distillation
jev
noul
choice
score
lora
qwen3_5
dual-head
vllm
multimodal
vision
computer-use
robotics
Eval Results (legacy)
Instructions to use autotrust/JEV-9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use autotrust/JEV-9B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="autotrust/JEV-9B")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("autotrust/JEV-9B") model = AutoModelForCausalLM.from_pretrained("autotrust/JEV-9B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
5 days ago
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Model card: AutoTrust/GuruSearch recommendation & search live demo (news.guru.so)
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Model card: autotrust/JEV recommendation & search live demo (news.guru.so)
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Model card: news search powered by autotrust/JEV (news.guru.so)
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Model card: JEV-powered news search is live (news.guru.so)
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6 days ago
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Model card: fix the ModelScope homepage sentence (real-time sync)
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Model card: ModelScope section — links only (no recommendation or install lines)
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Model card: ModelScope section heading without '(China)'
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Model card: ModelScope (China) download links — official AutoTrust-Labs homepage, real-time sync with this repository
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13 days ago
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JEV-9B can see: robot-arm and computer-use demos, vl/ (multimodal serving), image evaluations
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20 days ago
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Model card: aligned with JEV-27B — first integrated System 1 + System 2 model, Blocks of Experts recipe, KL fidelity, speed vs hosted API, comparison with other reproductions
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Model card: repository renamed to autotrust/JEV-9B; all ids, paths and commands updated
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autotrust/JEV: model weights, System 1 adapter + decision head, vLLM adapter, calibration and evaluation reports
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