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

base_model = AutoModelForCausalLM.from_pretrained("C:\Users\MGManchon\Documents\Codex\2026-06-02\goal-ablietra-gemma4-31b-dense-para\work\gemma4-12b-it-text-only")
model = PeftModel.from_pretrained(base_model, "apol/gemma4-12b-it-libre-benign-adapter")

Gemma 4 12B IT Libre Benign Adapter

This repository contains a LoRA adapter for google/gemma-4-12B-it.

The adapter was trained as a benign false-refusal reduction / local assistant tuning pass. It is not presented as an "abliterated", uncensored, or safety-control-removal model.

Contents

  • adapter_model.safetensors: PEFT LoRA adapter weights
  • adapter_config.json: PEFT adapter configuration
  • tokenizer.json, tokenizer_config.json, chat_template.jinja: tokenizer assets copied for convenience
  • EVAL_RESULTS.md: small direct evaluation report from local validation
  • FREEDOM_CRITERIA.md: benign local-assistant criteria used during the run

Intended Use

Use this adapter with users who already have access to the base model:

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel

base_id = "google/gemma-4-12B-it"
adapter_id = "apol/gemma4-12b-it-libre-benign-adapter"

tokenizer = AutoTokenizer.from_pretrained(base_id)
model = AutoModelForCausalLM.from_pretrained(base_id, device_map="auto")
model = PeftModel.from_pretrained(model, adapter_id)

Notes

This is a derived adapter for local experimentation. Use must comply with the base model license and terms. The adapter does not include the base model weights.

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