license: gemma
base_model: google/gemma-4-12B-it
library_name: transformers
pipeline_tag: any-to-any
tags:
- gemma4
- gemma-4-12b
- uncensored
- multimodal
- image-text-to-text
- research
Gemma4-12B-Uncensored
Gemma4-12B-Uncensored is a research-oriented derivative of google/gemma-4-12B-it, prepared for experiments on refusal behavior, over-refusal, and multimodal instruction-following robustness.
The checkpoint is released as a clean full-weight BF16 Gemma 4 unified model. It includes the standard tokenizer, chat template, and multimodal processor files required for text and image-conditioned text generation.
Model Details
| Field | Value |
|---|---|
| Model name | Gemma4-12B-Uncensored |
| Base model | google/gemma-4-12B-it |
| Format | Full checkpoint, BF16 safetensors |
| Architecture | Gemma 4 12B unified instruction model derivative |
| Interface | AutoProcessor + AutoModelForMultimodalLM / pipeline("any-to-any") |
| Primary use | Research on refusal suppression and controlled multimodal evaluation |
| Maintainer | Toan Doan |
| Contact | [email protected] |
Method
This model was produced with a post-training refusal-behavior modification pipeline. In short, the process identifies internal refusal-associated behavior and applies a targeted weight-space intervention to reduce refusal-style responses while preserving the original Gemma 4 unified multimodal interface.
Implementation details are intentionally summarized here; this repository is presented as a model release for controlled research and evaluation.
Quick Evaluation
Current multimodal smoke test uses PKU-Alignment/MM-SafetyBench, config Sex, with 20 random image-text samples from SD, SD_TYPO, and TYPO splits. Refusal is measured with a keyword-based detector; this is a quick operational check, not a complete safety or capability benchmark.
| Model | Samples | Errors ↓ | Refusal rate ↓ | Uncensored compliance ↑ | Image probe |
|---|---|---|---|---|---|
toandev/Gemma4-12B-Uncensored |
20 | 0 | 0.00% | 100.00% | 3/3 |
zaakirio/gemma-4-12b-it-uncensored |
20 | 0 | 0.00% | 100.00% | 3/3 |
Image probe: a simple red-rectangle recognition prompt, sampled with three fixed seeds. Evaluation seed: 20260611; max_new_tokens=96; dtype: torch_dtype="auto".
Usage
from transformers import AutoModelForMultimodalLM, AutoProcessor
import torch
model_id = "toandev/Gemma4-12B-Uncensored"
processor = AutoProcessor.from_pretrained(model_id)
model = AutoModelForMultimodalLM.from_pretrained(
model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{
"role": "user",
"content": [
{"type": "text", "text": "Explain the difference between over-refusal and safety refusal."}
],
}
]
inputs = processor.apply_chat_template(
messages,
tokenize=True,
return_dict=True,
return_tensors="pt",
add_generation_prompt=True,
).to(model.device)
with torch.inference_mode():
outputs = model.generate(**inputs, max_new_tokens=256)
print(processor.decode(outputs[0], skip_special_tokens=True))
For image-text prompts, pass an image item in content:
messages = [
{
"role": "user",
"content": [
{"type": "image", "image": image},
{"type": "text", "text": "Describe the image."},
],
}
]
Notes
This checkpoint is intended for research and controlled evaluation. Users are responsible for complying with the Gemma license, applicable platform policies, and local regulations.
Copyright
Copyright © 2026 Toan Doan. Contact: [email protected].
This model is a derivative of google/gemma-4-12B-it and remains subject to the upstream Gemma license and terms.