Model: mindchain/t5gemma2-sae-all-layers
Author: mindchain
Library: transformers
Tags: transformers, sae, sparse-autoencoder, t5gemma, t5gemma2, mechanistic-interpretability, activation-steering, steering, neuronpedia, gemma-scope, sae-lens, llm-interpretability, explainable-ai, xai, model-steering, feature-engineering, representation-learning, base_model:google/t5gemma-2-270m-270m, base_model:finetune:google/t5gemma-2-270m-270m, license:mit, endpoints_compatible, region:us
Base models (finetune): id: google/t5gemma-2-270m-270m
Card metadata: license: mit
library_name: transformers
base_model: google/t5gemma-2-270m-270m
colab: link: https://colab.research.google.com/github/haddock-development/t5gemma2-sae-all-layers/blob/main/colab.ipynb
title: T5Gemma 2 SAE - Quick Start
model_index: name: google/t5gemma-2-270m-270m
results: task: type: mechanistic-interpretability
dataset: type: custom
name: T5Gemma 2 SAE
metrics: name: SAE Checkpoints
value: 36
tags: sae, sparse-autoencoder, t5gemma, t5gemma2, mechanistic-interpretability, activation-steering, steering, neuronpedia, gemma-scope, sae-lens, llm-interpretability, explainable-ai, xai, model-steering, feature-engineering, representation-learning
Likes: 1 | All-time downloads: 0
Created: 2025-12-27 15:45:56