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model-organisms-for-real/olmo2_1b_sft_checkpoint_oracle_v1

sourceHugging Faceupdated 5mo 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: allenai/OLMo-2-0425-1B-SFT
—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("allenai/OLMo-2-0425-1B-SFT")
tokenizer = AutoTokenizer.from_pretrained("allenai/OLMo-2-0425-1B-SFT")

# Load LoRA adapter
model = PeftModel.from_pretrained(base_model, "model-organisms-for-real/olmo2_1b_sft_checkpoint_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.