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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
460 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
cloudyu's picture
cloudyu
v0.8.0 dual-head bundle: pristine Qwen3.5-9B backbone + lm_head (bit-identical, HumanEval 70.7% = base) + unmerged LoRA decision adapter + 24-slot head; card: one backbone two heads
448ef61 verified 36 minutes ago
  • configs
    Upload JEV v0.7.0 (Qwen3.5-9B distilled from Jev 1.13) 1 day ago
  • reports
    v0.8.0 dual-head bundle: pristine Qwen3.5-9B backbone + lm_head (bit-identical, HumanEval 70.7% = base) + unmerged LoRA decision adapter + 24-slot head; card: one backbone two heads 36 minutes ago
  • scripts
    v0.8.0 dual-head bundle: pristine Qwen3.5-9B backbone + lm_head (bit-identical, HumanEval 70.7% = base) + unmerged LoRA decision adapter + 24-slot head; card: one backbone two heads 36 minutes ago
  • src
    v0.8.0 dual-head bundle: pristine Qwen3.5-9B backbone + lm_head (bit-identical, HumanEval 70.7% = base) + unmerged LoRA decision adapter + 24-slot head; card: one backbone two heads 36 minutes ago
  • tests
    Upload JEV v0.7.0 (Qwen3.5-9B distilled from Jev 1.13) 1 day ago
  • DESIGN.md
    16.5 kB
    Upload JEV v0.7.0 (Qwen3.5-9B distilled from Jev 1.13) 1 day ago
  • README.md
    4.43 kB
    Upload JEV v0.7.0 (Qwen3.5-9B distilled from Jev 1.13) 1 day ago
  • pyproject.toml
    799 Bytes
    v0.8.0: continued training to 0.93 epoch with LR annealing — t30k KL 0.0276→0.0210, choice top-1 0.884→0.898, score MAE 0.119→0.103, ECE 0.0014→0.0007 1 day ago