thejaminator / gemma-hook-layer-0-step-3500

huggingface.co
Total runs: 5
24-hour runs: 0
7-day runs: 0
30-day runs: 4
Model's Last Updated: August 28 2025

Introduction of gemma-hook-layer-0-step-3500

Model Details of gemma-hook-layer-0-step-3500

LoRA Adapter for SAE Introspection

This is a LoRA (Low-Rank Adaptation) adapter trained for SAE (Sparse Autoencoder) introspection tasks.

Base Model
  • Base Model : google/gemma-2-9b-it
  • Adapter Type : LoRA
  • Task : SAE Feature Introspection
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel

# Load base model and tokenizer
base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2-9b-it")
tokenizer = AutoTokenizer.from_pretrained("google/gemma-2-9b-it")

# Load LoRA adapter
model = PeftModel.from_pretrained(base_model, "thejaminator/gemma-hook-layer-0-step-3500")
Training Details

This adapter was trained using the lightweight SAE introspection training script to help the model understand and explain SAE features through activation steering.

Runs of thejaminator gemma-hook-layer-0-step-3500 on huggingface.co

5
Total runs
0
24-hour runs
0
3-day runs
0
7-day runs
4
30-day runs

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gemma-hook-layer-0-step-3500 is an open source model from GitHub that offers a free installation service, and any user can find gemma-hook-layer-0-step-3500 on GitHub to install. At the same time, huggingface.co provides the effect of gemma-hook-layer-0-step-3500 install, users can directly use gemma-hook-layer-0-step-3500 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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