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chimingw/gemma-4-e2b-uncensored-hauhaucs-aggressive-q6-k-p-llamafile

chimingw Gemma GGUF multimodal second-order
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Abliteration classifier · v1.0.0
M8
Primary method

Repackaging (quantization)

Applied on top of direct removal inherited from the base model.
Confidence
MEDIUM
Inherited from base model
Why this label 3 signals
Method inferred from partial signals - repository name, related files, or tag patterns. Producer identity not confirmed; label may sharpen or shift as we gather more evidence.
  • 'abliterated' in name/tags
  • is_gguf=1
  • assume M1 (base ablation) + M8 (GGUF quant) - default when producer unknown
Refusal direction extraction

No specific extraction method could be identified for this model. The producer either did not document it or used a proprietary pipeline.

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Downloads · lifetime
120
23 last 30d - stable
Likes
0
Model age
8w ago
created 2026-08-15
Downloads over time
Now134→from7↑1,814%
149981477 on Aug 19134 on Oct 11AugSepOct
Aug 19 → Oct 11 · 48 snapshots · spans 53 days

Genealogy 0 direct forks

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This model's place in the market. Above: what it was derived from. Below: the tree of everything derived from it.

Metadata

License
gemma
Languages
en multilingual
Tags
llamafile gguf gemma4 multimodal vision audio uncensored abliterated quantized q6_k_p apple-silicon metal

Related

Total size
0 B
Files
4
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-08-15 06:37

Files by quantization

Auxiliary files 4 files 4.85 GB
Gemma-4-E2B-Uncensored-HauhauCS-Aggressive-Q6_K_P.llamafile 4.85 GB b06dd9ad download
LICENSE 10.6 KB 487a5552 download
README.md 6.67 KB 95c677d8 download
.gitattributes 1.58 KB f08652c8 download

README current version from Hugging Face


license: gemma
base_model: HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive
base_model_relation: quantized
pipeline_tag: image-text-to-text
inference: false
language:

  • en
  • multilingual
    tags:
  • llamafile
  • gguf
  • gemma4
  • multimodal
  • vision
  • audio
  • uncensored
  • abliterated
  • quantized
  • q6_k_p
  • apple-silicon
  • metal

Gemma-4-E2B Uncensored HauhauCS Aggressive Q6_K_P — llamafile

An unofficial, reproducible llamafile package of the Q6_K_P GGUF from HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive.

HauHauCS claims:

No changes to datasets or capabilities. Fully functional, 100% of what the original authors intended — just without the refusals.

These are meant to be the best lossless uncensored models out there.

Aggressive Variant

Stronger uncensoring — model is fully unlocked and won't refuse prompts. May occasionally append short disclaimers (baked into base model training, not refusals) but full content is always generated.

These are HauhauCS's claims. This package has not independently validated the claimed refusal behavior, capability preservation, or uncensoring results.

The single executable contains:

  • Gemma-4-E2B-Uncensored-HauhauCS-Aggressive-Q6_K_P.gguf;
  • mmproj-Gemma-4-E2B-Uncensored-HauhauCS-Aggressive-f16.gguf for supported multimodal input;
  • llamafile 0.10.5; and
  • terminal chat, browser chat, and a localhost API server.

The model and f16 projector were embedded without retraining, merging, re-quantization, or compression.

Intended use

This package is for people who want one downloadable executable containing a small, local Gemma 4 E2B model, its multimodal projector, a terminal chat interface, a browser chat interface, and a localhost API server. It is convenient for offline or self-contained macOS/Linux use where installing a separate inference runtime is undesirable.

Because everything is in one file, you can keep it on a USB drive and bring a self-contained local AI with you. According to HauhauCS's claim above, this aggressive variant is fully unlocked and does not refuse prompts. The destination computer still needs a supported 64-bit platform and enough RAM, and the drive or filesystem must permit executable files.

Included artifact

File Size SHA-256
Gemma-4-E2B-Uncensored-HauhauCS-Aggressive-Q6_K_P.llamafile 5,203,444,996 bytes (5.20 GB / 4.85 GiB) b06dd9ad6ebdda4fb9ba577924e219781460d4041214c0fc6b4f0dba524285cf

Embedded components and reproducibility tools

Component Size SHA-256
Gemma-4-E2B-Uncensored-HauhauCS-Aggressive-Q6_K_P.gguf 3,866,957,760 bytes 8dd59a0e2d917c1ba518db07c4012d9ac34e5d6ae10f8e209f2a4c43c55fe7b7
mmproj-Gemma-4-E2B-Uncensored-HauhauCS-Aggressive-f16.gguf 985,570,240 bytes 628b7e999f89beef70b32396ae84f59c096e867747d7901f0134064ff672e290
llamafile-0.10.5 runtime 350,768,862 bytes 417bcc3348cd5162c2751812fc0ea2f6e79e89e7be6f17e8401ed95de2ed4246
zipalign-0.10.5 build tool 851,513 bytes 7eac59c658226027b365d92131babf06341f746fb20c0db33115bbdf5c5c6c4b

Run

On macOS or Linux:

chmod +x Gemma-4-E2B-Uncensored-HauhauCS-Aggressive-Q6_K_P.llamafile
./Gemma-4-E2B-Uncensored-HauhauCS-Aggressive-Q6_K_P.llamafile

The terminal chat starts directly. While it is running, open the browser chat at:

http://127.0.0.1:8080/

The OpenAI-compatible API is available under:

http://127.0.0.1:8080/v1

The server is bound to localhost by default. Do not expose it publicly without authentication, TLS, and appropriate network controls.

Packaged defaults

  • model: /zip/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive-Q6_K_P.gguf;
  • projector: /zip/mmproj-Gemma-4-E2B-Uncensored-HauhauCS-Aggressive-f16.gguf;
  • context: 8,192 tokens;
  • sampler: temperature 0.6, top-p 0.95, top-k 20, min-p 0.0;
  • Jinja chat templates enabled;
  • supported multimodal input enabled through the embedded f16 projector; and
  • additional command-line arguments pass through after the embedded defaults.

To override the context size, pass --ctx-size when launching; for example:

./Gemma-4-E2B-Uncensored-HauhauCS-Aggressive-Q6_K_P.llamafile --ctx-size 32768

Larger contexts increase memory use. The upstream GGUF advertises a native context length of 131,072 tokens, but practical limits depend on the runtime, KV-cache settings, and available memory.

Multimodality and architecture

The f16 projector is paired with the main GGUF inside the executable. The HauhauCS card describes Gemma 4 E2B as natively multimodal for text, image, video, and audio and states that vision/audio use requires the projector. Actual media handling still depends on the input client and the capabilities exposed by llamafile 0.10.5.

The original lineage is google/gemma-4-e2b-it. Its E2B architecture has 35 layers, 512-token sliding-window attention interleaved with full attention, and a 128K-class context window (131,072 tokens in this GGUF's metadata). Google's original card describes 2.3B effective parameters, or 5.1B including embeddings.

Provenance

Notes

  • This is an unofficial repackaging, not a new model release.
  • The embedded projector makes the package multimodal; image, audio, and video handling still depends on client/UI and embedded-runtime support.
  • The upstream repository describes the model as aggressively uncensored. This package does not independently reproduce or validate its refusal or capability claims.
  • The packaged 8,192-token default is conservative. Override it with --ctx-size N, such as --ctx-size 32768, if your memory budget permits.
  • This full-runtime artifact is larger than 4 GiB, so it is intended primarily for macOS and Linux rather than direct execution on Windows.
  • Hugging Face hosted inference is disabled because this repository distributes a standalone executable rather than a standard hosted-inference checkpoint.

README history 1 version

The author's README evolved over time. Click a version to see its content at that point.

  1. 2026-08-15Add model card and license56418ec6.7 KB
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