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autotrust
/
JEV

Text Classification
Transformers
Safetensors
English
qwen3_5_text
text-generation
system-one
typed-decisions
decision-model
calibrated-probabilities
knowledge-distillation
jev
noul
choice
score
lora
qwen3_5
dual-head
Eval Results (legacy)
Model card Files Files and versions
xet
Community

Instructions to use autotrust/JEV with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use autotrust/JEV with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="autotrust/JEV")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("autotrust/JEV")
    model = AutoModelForCausalLM.from_pretrained("autotrust/JEV", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
JEV / code /configs
2.91 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
cloudyu's picture
cloudyu
Upload JEV v0.7.0 (Qwen3.5-9B distilled from Jev 1.13)
b2f3bf4 verified 2 days ago
  • train.yaml
    1.02 kB
    Upload JEV v0.7.0 (Qwen3.5-9B distilled from Jev 1.13) 2 days ago
  • train_27b.yaml
    722 Bytes
    Upload JEV v0.7.0 (Qwen3.5-9B distilled from Jev 1.13) 2 days ago
  • train_s1.yaml
    522 Bytes
    Upload JEV v0.7.0 (Qwen3.5-9B distilled from Jev 1.13) 2 days ago
  • train_smoke.yaml
    646 Bytes
    Upload JEV v0.7.0 (Qwen3.5-9B distilled from Jev 1.13) 2 days ago