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autotrust
/
JEV-35B-NVFP4

Text Classification
Transformers
Safetensors
English
qwen3_5_moe
image-text-to-text
system-one
typed-decisions
decision-model
calibrated-probabilities
jev
noul
choice
score
lora
mixture-of-experts
vllm
nvfp4
modelopt
fp4
Eval Results (legacy)
8-bit precision
Model card Files Files and versions
xet
Community

Instructions to use autotrust/JEV-35B-NVFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use autotrust/JEV-35B-NVFP4 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="autotrust/JEV-35B-NVFP4")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoProcessor, AutoModelForMultimodalLM
    
    processor = AutoProcessor.from_pretrained("autotrust/JEV-35B-NVFP4")
    model = AutoModelForMultimodalLM.from_pretrained("autotrust/JEV-35B-NVFP4", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
JEV-35B-NVFP4 / reports
340 kB
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  • 1 contributor
History: 1 commit
cloudyu's picture
cloudyu
Add files using upload-large-folder tool
a2a6040 verified 13 days ago
  • demos-nvfp4
    Add files using upload-large-folder tool 13 days ago
  • demos
    Add files using upload-large-folder tool 13 days ago