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autotrust
/
GEV-26B-Decide

Text Classification
Transformers
Safetensors
English
gemma4
image-text-to-text
system-one
system-two
adaptive-thinking
typed-decisions
decision-model
calibrated-probabilities
jev
noul
choice
score
lora
mixture-of-experts
multimodal
vllm
Eval Results (legacy)
Model card Files Files and versions
xet
Community
2

Instructions to use autotrust/GEV-26B-Decide with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use autotrust/GEV-26B-Decide with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="autotrust/GEV-26B-Decide")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoProcessor, AutoModelForMultimodalLM
    
    processor = AutoProcessor.from_pretrained("autotrust/GEV-26B-Decide")
    model = AutoModelForMultimodalLM.from_pretrained("autotrust/GEV-26B-Decide", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Dataset used?

2
#2 opened about 18 hours ago by
SargeDev

MLX port for Apple silicon (System 1): Avicennasis/GEV-26B-Decide-mlx-8bit / -4bit

👍 3
3
#1 opened 3 days ago by
Avicennasis
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