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spatial-neural-feature-accentuation-checkpoints
binxu/spatial-neural-feature-accentuation-checkpoints
spatial-neural-feature-accentuation-checkpoints is a feature extraction model from binxu. Use it when you need embeddings to search or compare text. It is set up for torchvision. The card lists the license as other.
Runtime artifacts for Animadversio/spatial-neural-feature-accentuation.
Access
Public
Updated Aug 25, 2026
Repo size
115 MB
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Repo makeup
Click a slice to open those files.
.pt115 MB · 100%
At a glance
- Task
- Feature Extraction
- Library
- torchvision
- License
- other
- Access
- Public
- Created
- Aug 25, 2026
- Updated
- Aug 25, 2026
- SHA
- c1d27bfe
Model card
From the Hugging Face model README
Spatial Neural Feature Accentuation checkpoints
Runtime artifacts for Animadversio/spatial-neural-feature-accentuation.
Files
| File | Purpose | SHA-256 |
|---|---|---|
resnet50_robust_backbone.pt | Adversarially robust ImageNet ResNet-50 state dict | 6c6731b622d6e521d4e36707f5a0d24d18ff7d8ffee1ac30b7a68eb36871c763 |
resnet50_robust_25_compiled_targets.pt | 25 PCA/readout objectives collapsed to feature-space weights and biases | 69975cfdf5abaaecfaf34ea76d05b02f93bc2d4f13a195d99b3652a1f7b24757 |
The compiled cache contains five selected neural-encoding targets for each of
five monkeys (leap, paul, red, three0, and venus). Internal filesystem
paths have been removed from this publication copy. It retains target IDs,
subject labels, unit IDs, robust-ResNet layer names, effective weights/biases,
and q01/q99 response normalization values.
Use
The companion repository downloads these files at a pinned Hub revision and checks both SHA-256 hashes before loading them. They can also be downloaded with:
hf download binxu/spatial-neural-feature-accentuation-checkpoints \
--include 'resnet50_robust_*.pt' \
--local-dir checkpoints
These files are intended for differentiable feature visualization and the research-art workflow documented in the companion repository. The 25 compiled targets are not general-purpose image classifiers.
Licenses and provenance
The companion code is MIT licensed. These weight artifacts retain the terms of their original models and source data; users are responsible for complying with those terms. See the companion repository for method details, limitations, privacy guidance, target definitions, and reproducibility metadata.
- Task
- Feature Extraction
- Library
- torchvision
- License
- other
- Created
- Aug 25, 2026
- Updated
- Aug 25, 2026