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
Eval Results (legacy)
Eval Results
Instructions to use autotrust/JEV-27B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use autotrust/JEV-27B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="autotrust/JEV-27B")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("autotrust/JEV-27B") model = AutoModelForCausalLM.from_pretrained("autotrust/JEV-27B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model card: autotrust/JEV recommendation & search live demo (news.guru.so)
Browse files
README.md
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# autotrust/JEV-27B
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**[autotrust/JEV-27B-VL](https://huggingface.co/autotrust/JEV-27B-VL)**, autotrust/JEV-27B with vision, is now online.
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# autotrust/JEV-27B
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[](https://news.guru.so/ui)
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## 🔴 Live: autotrust/JEV recommendation & search demo → [news.guru.so](https://news.guru.so/ui)
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> [!IMPORTANT]
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> **Try autotrust/JEV live (new, 11 October 2026).** A recommendation and search demo in which every ranking is made by
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> **[autotrust/JEV-27B](https://huggingface.co/autotrust/JEV-27B)** System 1 decisions, in about half a second:
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> * **Recommendation:** the latest headlines from 6 news feeds, ranked by importance.
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> * **Search:** results from Google News, Bing News and Yahoo News re-ranked by relevance, side by side with the
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> search engines' own order, plus a short answer with citations.
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**[autotrust/JEV-27B-VL](https://huggingface.co/autotrust/JEV-27B-VL)**, autotrust/JEV-27B with vision, is now online.
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