How to use from the
Use from the
PEFT library
from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-Coder-32B-Instruct")
model = PeftModel.from_pretrained(base_model, "Jordine/qwen32b-ao-v1-step-500")

LoRA Adapter for SAE Introspection

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

Base Model

  • Base Model: Qwen/Qwen2.5-Coder-32B-Instruct
  • 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("Qwen/Qwen2.5-Coder-32B-Instruct")
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2.5-Coder-32B-Instruct")

# Load LoRA adapter
model = PeftModel.from_pretrained(base_model, "Jordine/qwen32b-ao-v1-step-500")

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.

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