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harc-ablation-adapters
autoRiver/harc-ablation-adapters
harc-ablation-adapters is a machine learning model from autoRiver. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This repository contains the ten public LoRA adapters from the HARC ablation experiment. Each subdirectory is an independent adapter and can be loaded with its corresponding base model.
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Updated Jul 28, 2026
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At a glance
- Access
- Public
- Created
- Jul 28, 2026
- Updated
- Jul 28, 2026
- SHA
- 9a6d3e50
Model card
From the Hugging Face model README
HARC ablation LoRA adapters
This repository contains the ten public LoRA adapters from the HARC ablation experiment. Each subdirectory is an independent adapter and can be loaded with its corresponding base model.
Adapters
| Directory | Base model | KL coefficient | Margin |
|---|---|---|---|
qwen_kl10_m03 | Qwen/Qwen2.5-7B-Instruct | 10 | 0.3 |
qwen_kl10_m07 | Qwen/Qwen2.5-7B-Instruct | 10 | 0.7 |
qwen_kl5_m05 | Qwen/Qwen2.5-7B-Instruct | 5 | 0.5 |
qwen_kl1_m05 | Qwen/Qwen2.5-7B-Instruct | 1 | 0.5 |
qwen_kl20_m05 | Qwen/Qwen2.5-7B-Instruct | 20 | 0.5 |
llama_kl10_m03 | meta-llama/Llama-3.1-8B-Instruct | 10 | 0.3 |
llama_kl10_m07 | meta-llama/Llama-3.1-8B-Instruct | 10 | 0.7 |
llama_kl1_m05 | meta-llama/Llama-3.1-8B-Instruct | 1 | 0.5 |
llama_kl5_m05 | meta-llama/Llama-3.1-8B-Instruct | 5 | 0.5 |
llama_kl20_m05 | meta-llama/Llama-3.1-8B-Instruct | 20 | 0.5 |
All adapters use LoRA rank 32 and alpha 64. The training source was the
harc-ablate-qwen-llama-0727 AMLT experiment in the sft4safety project.
Loading an adapter
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
base_model = "Qwen/Qwen2.5-7B-Instruct"
adapter_repo = "autoRiver/harc-ablation-adapters"
adapter_subfolder = "qwen_kl10_m03"
tokenizer = AutoTokenizer.from_pretrained(base_model)
model = AutoModelForCausalLM.from_pretrained(
base_model,
torch_dtype=torch.bfloat16,
device_map="auto",
)
model = PeftModel.from_pretrained(
model,
adapter_repo,
subfolder=adapter_subfolder,
)
For the llama_* adapters, use
meta-llama/Llama-3.1-8B-Instruct as base_model.
The base model remains subject to its original Hugging Face access license.
- Created
- Jul 28, 2026
- Updated
- Jul 28, 2026