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akhilaaa3
/
Jev-Omni

Text Classification
Transformers
Safetensors
gemma4_unified
image-text-to-text
multimodal
merged
Model card Files Files and versions
xet
Community
1

Instructions to use akhilaaa3/Jev-Omni with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use akhilaaa3/Jev-Omni with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="akhilaaa3/Jev-Omni")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoProcessor, AutoModelForMultimodalLM
    
    processor = AutoProcessor.from_pretrained("akhilaaa3/Jev-Omni")
    model = AutoModelForMultimodalLM.from_pretrained("akhilaaa3/Jev-Omni", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
Jev-Omni / assets
20.4 MB
Ctrl+K
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  • 1 contributor
History: 3 commits
akhilaaa3's picture
akhilaaa3
The Wall: 23-second demo film (11 cameras, voicemails, chats on one GPU)
cb4a0ff verified 15 days ago
  • medium-accuracy.png
    79.9 kB
    xet
    Simplify model card and add merged Jev-Omni Medium accuracy and calibration plots 16 days ago
  • medium-accuracy.svg
    4.03 kB
    Simplify model card and add merged Jev-Omni Medium accuracy and calibration plots 16 days ago
  • medium-calibration.png
    140 kB
    xet
    Simplify model card and add merged Jev-Omni Medium accuracy and calibration plots 16 days ago
  • medium-calibration.svg
    5.03 kB
    Simplify model card and add merged Jev-Omni Medium accuracy and calibration plots 16 days ago
  • the-wall-23s.mp4
    20.2 MB
    xet
    The Wall: 23-second demo film (11 cameras, voicemails, chats on one GPU) 15 days ago