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mzx
/
NEvo

Text-to-Video
Diffusers
NevoPipeline
neuroscience
fmri
brain-decoding
stimulus-synthesis
v-jepa
Model card Files Files and versions
xet
Community

Instructions to use mzx/NEvo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use mzx/NEvo with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("mzx/NEvo", dtype=torch.bfloat16, device_map="cuda")
    
    prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
    image = pipe(prompt).images[0]
  • Notebooks
  • Google Colab
  • Kaggle
NEvo / tests
Ctrl+K
Ctrl+K
  • 2 contributors
History: 10 commits
mzx's picture
mzx
Add image-only pipeline mode
81ab95d about 23 hours ago
  • test_asset_scoring.py
    2.55 kB
    Publish self-contained NEVO stimulus-synthesis pipeline + model card 6 days ago
  • test_output_schema.py
    1.01 kB
    Publish self-contained NEVO stimulus-synthesis pipeline + model card 6 days ago
  • test_prompt_space.py
    594 Bytes
    Publish self-contained NEVO stimulus-synthesis pipeline + model card 6 days ago
  • test_robust_transform.py
    2.1 kB
    Align two-stage search with canonical: clean scoring, art_data stage-1, image/video batching 4 days ago
  • test_roi_search_space.py
    1.9 kB
    Expose encoder input resolution as score_size (default 224) 4 days ago
  • test_seeded_asset_search.py
    6.84 kB
    Expose encoder input resolution as score_size (default 224) 4 days ago
  • test_smoke_pipeline.py
    1.88 kB
    Add image-only pipeline mode about 23 hours ago
  • test_video_normalize.py
    877 Bytes
    Publish self-contained NEVO stimulus-synthesis pipeline + model card 6 days ago