gemma-4-E4B-it-ultra-uncensored-heretic
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Gemma-4-E4B-Uncensored-HauhauCS-Aggressive
Gemma-4-E4B-Uncensored-HauhauCS-Aggressive is a abliterated and uncensored variant of HauhauCS/Gemma-4-E4B-Uncensored-HauhauCS-Aggressive, published on Hugging Face by joe-speedobat. It is distributed across 52 repositories in GGUF, NVFP4 and Transformers formats, totalling 757.6K downloads.
Specification
- Model name
- Gemma-4-E4B-Uncensored-HauhauCS-Aggressive
- Source repository
- joe-speedobat/Gemma-4-E4B-Uncensored-HauhauCS-Aggressive
- Publisher
- joe-speedobat
- Parameters
- Not determinable from name
- VRAM required
- Unknown — no published parameter count
- Hardware class
- Unknown
- Licence
- Not declared
- Task
- Unspecified
- Context window
- Not documented
- Ablation scope
- Not stated by the publisher
- Formats available
- GGUF, NVFP4, Transformers
- First indexed
- 2 Apr 2026
- Last updated
- 20 Oct 2026
Ablation technique
How Gemma-4-E4B-Uncensored-HauhauCS-Aggressive was modified, and what that implies.
Abliteration + uncensored fine-tune
Directional ablation combined with additional fine-tuning on unfiltered data, so behaviour diverges from the base model beyond refusal removal alone.
Reported scope: Not stated by the publisher. Publishers frequently omit this, so verify behaviour empirically rather than assuming full coverage.
Running it
Commands are templates — confirm the exact repository and quant file before use.
llama.cpp / GGUF
hf download HauhauCS/Gemma-4-E4B-Uncensored-HauhauCS-Aggressive --local-dir ./gemma-4-e4b-uncensored-hauhaucs-aggressive
llama-cli -m ./gemma-4-e4b-uncensored-hauhaucs-aggressive/<file>.gguf -p "..."Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer
repo = "joe-speedobat/Gemma-4-E4B-Uncensored-HauhauCS-Aggressive"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
repo, torch_dtype="auto", device_map="auto"
)vLLM
vllm serve joe-speedobat/Gemma-4-E4B-Uncensored-HauhauCS-Aggressive --trust-remote-codeDownloads and variants (51)
Every published repository of Gemma-4-E4B-Uncensored-HauhauCS-Aggressive, 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-E4B-Uncensored-HauhauCS-Aggressive 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.
- This release adds fine-tuning on unfiltered data, so its behaviour diverges from the base model beyond refusal removal — differences you measure cannot be attributed to ablation alone.
- No licence is declared on this repository, which is a compliance problem in itself. Resolve it against the base model’s terms before use.
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-E4B-Uncensored-HauhauCS-Aggressive is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with joe-speedobat, and does not independently verify publisher claims. See responsible use.