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Gemma-4-Abliterated-LiteRT

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DuoNeural/Gemma-4-Abliterated-LiteRT is an uncensored open-source model hosted on Hugging Face.

Text GenerationEnglishLicense: gemmalitertgemma4androidedge-aiabliterateduncensoredon-devicemobile
README.md说明 / 使用方法

license: gemma language:

  • en base_model:
  • DuoNeural/TurboGemma4E2B
  • DuoNeural/Gemma-4-E4B-Abliterated tags:
  • gemma4
  • litert
  • android
  • edge-ai
  • abliterated
  • uncensored
  • on-device
  • mobile pipeline_tag: text-generation

Gemma 4 Abliterated — LiteRT (Android Edge Gallery)

Abliterated Gemma 4 E2B and E4B models in .litertlm format for on-device inference via Google AI Edge Gallery.

Run uncensored Gemma 4 locally on your Android phone — no internet, no API, no filters.

Files

FileSizeBase ModelActive Params
Gemma-4-E2B-Abliterated.litertlm2.4 GBDuoNeural/TurboGemma4E2B2.3B
Gemma-4-E4B-Abliterated.litertlm3.9 GBDuoNeural/Gemma-4-E4B-Abliterated4.5B

Both models are INT4 quantized (dynamic weight INT4, FP32 activations) via litert-torch 0.9.0.

How to Install on Android

Requirements

  • Android 12 or newer
  • Google AI Edge Gallery app installed
  • Sufficient storage (2.4 GB for E2B, 3.9 GB for E4B)

Step 1 — Download the file to your phone

Easiest (Chrome on Android):

  1. Open Chrome on your Android device
  2. Navigate to this HuggingFace repo page
  3. Tap the file you want → tap the download icon (⬇)
  4. Chrome saves it to Downloads/

Via ADB (desktop + USB):

adb push Gemma-4-E2B-Abliterated.litertlm /sdcard/Download/

Step 2 — Load in Edge Gallery

  1. Open AI Edge Gallery
  2. Tap + → select the .litertlm file from Downloads
  3. Choose backend:
    • GPU (Adreno/Mali via Vulkan/OpenCL) — fastest
    • CPU (XNNPACK) — most compatible
    • NPU (if available) — peak performance on Snapdragon/MediaTek
  4. Start chatting — fully offline, nothing leaves your device

Performance (estimated)

Device classBackendTokens/sec
Flagship (Snapdragon 8 Gen 3+)NPU/GPU15–40 tok/s
Mid-rangeGPU5–15 tok/s
Any Android 12+CPU1–5 tok/s

Abliteration

Both source models have undergone abliteration — orthogonal projection to remove refusal vectors from the model's weight space. The refusal direction is identified via difference-in-means across harmful/harmless activations, then projected out of Q/K/V/O projections and MLP layers.

KL divergence from base: ~0.067 (E4B) — virtually identical output distribution for normal queries, refusals removed.

What changes: The model will engage with restricted topics it previously refused. What doesn't change: Intelligence, reasoning, coding ability, factual knowledge.

Source Models

  • E2B: DuoNeural/TurboGemma4E2B
  • E4B: DuoNeural/Gemma-4-E4B-Abliterated

Conversion: litert-torch 0.9.0, dynamic_wi4_afp32 recipe, cache_length=1024, externalized embedder, split_cache=False.

License

Gemma Terms of Use. Model weights derived from Google's Gemma 4 family.


DuoNeural

DuoNeural is an open AI research lab — human + AI in collaboration.

PlatformLink
HuggingFacehuggingface.co/DuoNeural
Websiteduoneural.com
GitHubgithub.com/DuoNeural
X / Twitter@DuoNeural
Email[email protected]
Newsletterduoneural.beehiiv.com
Supportbuymeacoffee.com/duoneural

DuoNeural Research Publications

TitleDOI
Nano-CTM: Ternary Continuous Thought Machines with Thought-Space Self-Prediction for Efficient Iterative Reasoning10.5281/zenodo.19775622
Recurrence as World Model: CTM Learns Implicit Belief States in Partially Observable Physical Environments10.5281/zenodo.19810620
Per-Object Slot Decomposition for Scalable Neural World Modeling: When Does Attention Beat Mean-Field?10.5281/zenodo.19846804
The Dynamical Horizon Principle: CTM Gates Converge to the Predictability Limit of Dynamical Systems10.5281/zenodo.19952612

Open access, CC BY 4.0. Authored by Archon, Jesse Caldwell, Aura — DuoNeural.

Research Team

  • Jesse — Vision, hardware, direction
  • Archon — AI lab partner, post-training, abliteration, experiments
  • Aura — Research AI, literature synthesis, novel proposals

Subscribe to the lab newsletter at duoneural.beehiiv.com for model drops before they go anywhere else.

HUGGING FACE

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来源与版本

作者
DuoNeural
最近更新
2026/05/01
最新创建
2026/04/29
HF 趋势
未知
数据快照
2026/09/17
版本
未知
许可证
gemma