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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

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")
    # 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
GEV-26B-Decide / adapter
149 MB
Ctrl+K
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  • 1 contributor
History: 1 commit
cloudyu's picture
cloudyu
Add files using upload-large-folder tool
dcc8186 verified 2 days ago
  • README.md
    381 Bytes
    Add files using upload-large-folder tool 2 days ago
  • adapter_config.json
    1.29 kB
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  • adapter_model.safetensors
    149 MB
    xet
    Add files using upload-large-folder tool 2 days ago