---
base_model: models/gemma-2-9b-it-taboo-chair-merged
library_name: peft
---

# 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-chair-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-chair-merged")
tokenizer = AutoTokenizer.from_pretrained("models/gemma-2-9b-it-taboo-chair-merged")

# Load LoRA adapter
model = PeftModel.from_pretrained(base_model, "model-organisms-for-real/gemma2_9b_it_taboo_chair_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.