Model: orrav/sae-clip-b32-x64-layer10-resid-post-cls-lr1e-2
Author: orrav
Pipeline: feature-extraction
Library: torch
Tags: torch, clip, vision, transformers, interpretability, sparse autoencoder, sae, mechanistic interpretability, feature-extraction, en, region:us
Card metadata: language: en
tags: clip, vision, transformers, interpretability, sparse autoencoder, sae, mechanistic interpretability
library_name: torch
pipeline_tag: feature-extraction
metrics: type: explained_variance
value: 89.42
pretty_name: Explained Variance %
range: min: 0
max: 100, type: l0
value: 655.9
pretty_name: L0
Likes: 0 | All-time downloads: 31
Created: 2025-06-09 06:39:02