gemma-4-E2B-it-ultra-uncensored-heretic
Gemmaheretic
from google/gemma-4-E2B-it
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gemma-4-E2B-it-heretic-ara
gemma-4-E2B-it-heretic-ara is a Heretic-ablated variant of google/gemma-4-E2B-it, published on Hugging Face by p-e-w. It is apache-2.0 licence. It is distributed across 23 repositories in Transformers, GGUF, MLX and GGUF (imatrix) formats, totalling 6.7K downloads.
Specification
- Model name
- gemma-4-E2B-it-heretic-ara
- Source repository
- p-e-w/gemma-4-E2B-it-heretic-ara
- Base model
- google/gemma-4-E2B-it
- Publisher
- p-e-w
- Parameters
- Not determinable from name
- Hardware class
- Unknown
- Licence
- apache-2.0
- Task
- Any to any
- Context window
- 128K tokens (as documented)
- Ablation scope
- Not stated by the publisher
- Formats available
- Transformers, GGUF, MLX, GGUF (imatrix)
- First indexed
- 2 Apr 2026
- Last updated
- 18 Aug 2026
Ablation technique
How gemma-4-E2B-it-heretic-ara was modified, and what that implies.
Heretic
Automated directional ablation via the Heretic toolchain, which searches for the refusal direction and applies it with a KL-divergence budget so general capability is preserved.
Reported scope: Not stated by the publisher. Publishers frequently omit this, so verify behaviour empirically rather than assuming full coverage.
From the publisher’s model card
“Gemma is a family of open models built by Google DeepMind. Gemma 4 models are multimodal, handling text and image input (with audio supported on small models) and generating text output. This release includes open-weights models in both pre-trained and instruction-tuned variants. Gemma 4 features a context window of...”
Running it
Commands are templates — confirm the exact repository and quant file before use.
llama.cpp / GGUF
hf download mradermacher/gemma-4-E2B-it-heretic-ara-GGUF --local-dir ./gemma-4-e2b-it-heretic-ara
llama-cli -m ./gemma-4-e2b-it-heretic-ara/<file>.gguf -p "..."Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer
repo = "p-e-w/gemma-4-E2B-it-heretic-ara"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
repo, torch_dtype="auto", device_map="auto"
)vLLM
vllm serve p-e-w/gemma-4-E2B-it-heretic-ara --trust-remote-codeDownloads and variants (22)
Every published repository of gemma-4-E2B-it-heretic-ara, including quantised re-releases by other authors.
Security-team assessment
Derived from this model’s metadata and the publisher’s claims — not from benchmarks run by this site.
- gemma-4-E2B-it-heretic-ara will attempt offensive-security prompts that a hosted commercial model declines, which is what makes it usable for red-team corpus generation and for measuring what an unaligned model of this class produces.
- The publisher does not state which layers were ablated, so assume nothing about refusal consistency — probe it directly.
- Declared licence is apache-2.0, but the terms that bind you are google/gemma-4-E2B-it’s — a re-release cannot grant more than its parent.
Handling: run it isolated, put moderation in front of it if anyone outside your team can reach it, and verify the weights before loading — these are third-party artifacts. Full handling and licence guidance.
Metadata for gemma-4-E2B-it-heretic-ara is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with p-e-w, and does not independently verify publisher claims. See responsible use.