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model-organisms-for-real/gemma2_9b_it_taboo_cloud_oracle_v1

sourceHugging Faceupdated 3mo agoView on Hugging Face

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LoRA Adapter for SAE Introspection

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

Base Model

—Base Model: models/gemma-2-9b-it-taboo-cloud-merged
—Adapter Type: LoRA
—Task: SAE Feature Introspection

Usage

python

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel

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

# Load LoRA adapter
model = PeftModel.from_pretrained(base_model, "model-organisms-for-real/gemma2_9b_it_taboo_cloud_oracle_v1")

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.