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Prisma-Multimodal
/
sparse-autoencoder-clip-b-32-sae-vanilla-x64-layer-10-hook_resid_post-l1-5e-05

Feature Extraction
Transformers
English
torch
clip
vision
interpretability
sparse autoencoder
sae
mechanistic interpretability
Model card Files Files and versions
xet
Community

Instructions to use Prisma-Multimodal/sparse-autoencoder-clip-b-32-sae-vanilla-x64-layer-10-hook_resid_post-l1-5e-05 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Prisma-Multimodal/sparse-autoencoder-clip-b-32-sae-vanilla-x64-layer-10-hook_resid_post-l1-5e-05 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="Prisma-Multimodal/sparse-autoencoder-clip-b-32-sae-vanilla-x64-layer-10-hook_resid_post-l1-5e-05")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("Prisma-Multimodal/sparse-autoencoder-clip-b-32-sae-vanilla-x64-layer-10-hook_resid_post-l1-5e-05", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
sparse-autoencoder-clip-b-32-sae-vanilla-x64-layer-10-hook_resid_post-l1-5e-05
302 MB
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  • 1 contributor
History: 3 commits
soniajoseph's picture
soniajoseph
Upload SAE model
67c5e77 verified over 1 year ago
  • .gitattributes
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    initial commit over 1 year ago
  • config.json
    2.25 kB
    Upload config over 1 year ago
  • n_images_2600058.pt

    Detected Pickle imports (3)

    • "torch.FloatStorage",
    • "torch._utils._rebuild_tensor_v2",
    • "collections.OrderedDict"

    What is a pickle import?

    302 MB
    xet
    Upload SAE model over 1 year ago