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Andycurrent/gemma-3-4b-it-uncensored-v2-GGUF

Andycurrent Gemma 4B GGUF second-order 131K ctx
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Response includes
  • classification m-uncensored
  • files 9
  • hub_downloads_all_time 49,584
  • author_summary 13 models
  • readme_text full
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Abliteration classifier · v1.0.0
M-U
Primary method

Uncensored (method unknown)

No other method signals detected in this model.
Confidence
LOW
Why this label 3 signals
Weak or ambiguous signals. Best guess based on catalog patterns; treat as tentative and check the evidence below.
  • 'uncensored' in name/tags but no 'abliterated' marker
  • method not identifiable from author declaration alone
  • may be DPO fine-tune, prompt engineering, or unknown technique
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
50K
2K last 30d - cooling
Likes
31
Model age
9mo ago
created 2026-01-06
Downloads over time
Now50.3K→from384↑13,005%
018.4K36.9K55.3K384 on Jan 750.3K on Oct 11JanMarMayJulSep
Jan 7 → Oct 11 · 82 snapshots · spans 277 days

Genealogy 0 direct forks

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Metadata

License
gemma
Languages
en
Quantizations
F16 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
gguf uncensored text-generation agent gemma en base_model:braindao/gemma-3-4b-it-uncensored-v2 base_model:quantized:braindao/gemma-3-4b-it-uncensored-v2 license:gemma endpoints_compatible region:us conversational

Related

Total size
22.6 GB
Files
9
Quantizations
8
Registered
2026-08-22 13:56
Last updated on HF
2026-01-19 12:39

Files by quantization

F16 1 file 7.23 GB
gemma-3-4b-it-uncensored-v2_F16.gguf 7.23 GB f3b5b4df download
Q8_0 1 file 3.85 GB
gemma-3-4b-it-uncensored-v2_Q8_0.gguf 3.85 GB a55c7fec download
Q6_K 1 file 2.97 GB
gemma-3-4b-it-uncensored-v2_Q6_K.gguf 2.97 GB 3a8a8784 download
Q5_K 1 file 2.64 GB
gemma-3-4b-it-uncensored-v2_Q5_K_M.gguf 2.64 GB 9961efc5 download
Q4_K 1 file 2.32 GB
gemma-3-4b-it-uncensored-v2_Q4_K_M.gguf 2.32 GB 6322e3af download
Q3_K 1 file 1.95 GB
gemma-3-4b-it-uncensored-v2_Q3_K_M.gguf 1.95 GB dedf7717 download
Q2_K 1 file 1.61 GB
gemma-3-4b-it-uncensored-v2_Q2_K.gguf 1.61 GB bde01a99 download
Auxiliary files 2 files 5.40 KB
README.md 3.41 KB ac2e79fa download
.gitattributes 1.99 KB 3ce0105e download

README current version from Hugging Face


license: gemma
language:

  • en
    base_model:
  • braindao/gemma-3-4b-it-uncensored-v2
    tags:
  • uncensored
  • text-generation
  • agent
  • gemma

Gemma-3-4B-IT-Uncensored-v2

This repository contains Quantized versions of Gemma 3 4B IT Uncensored v2, an instruction-tuned 4B parameter language model designed for users who want a highly responsive, minimally restricted assistant suitable for local, offline, or private deployments.
The model is optimized for direct interaction, reasoning, creative tasks, and experimentation, while preserving the efficiency and accessibility of a smaller parameter count.


Model Overview

  • Model Name: Gemma_3_4B_IT_Uncensored_v2
  • Base Architecture: Gemma 3 (4B parameters)
  • License: Inherits the license terms of the original Gemma 3 model
  • Intended Use: Local or private deployments where users want greater control over alignment, filtering behavior, and conversational tone

What Is Gemma 3 4B IT Uncensored v2?

Gemma-3-4B-IT-Uncensored-v2 is a lightly-aligned, instruction-following model focused on:

  • User-directed alignment
  • Reduced artificial guardrails
  • High responsiveness and clarity
  • Strong reasoning and step-by-step task handling
  • Efficient inference on consumer hardware

This version (v2) refines response quality, instruction adherence, and conversational stability compared to earlier releases, making it suitable for both casual and advanced users.


Chat Template & Conversation Format

The model follows a Gemma-style instruction format, typically structured as:

<start_of_turn>user
Your prompt here
<end_of_turn>
<start_of_turn>model

Using the correct chat template is strongly recommended for optimal instruction-following and response quality.


Key Features & Capabilities

  • Instruction-tuned for clear, concise, and user-aligned responses
  • Uncensored behavioral tuning for research and experimentation
  • Effective at conversational, creative, and reasoning tasks
  • Supports multi-step reasoning and structured answers
  • Optimized for local inference (CPU and GPU friendly)
  • Stable output across longer conversations
  • Suitable for alignment research and prompt engineering

Intended Use Cases

  • Local assistants – personal chatbots, productivity tools, role-play systems
  • Coding support – explanations, examples, lightweight debugging
  • Reasoning tasks – logical breakdowns, step-by-step problem solving
  • Creative writing – stories, dialogue, brainstorming
  • Experimentation – uncensored model behavior, alignment testing
  • Offline / private use – scenarios requiring data locality and user control

Hardware & Performance Notes

With only 4B parameters, this model is well-suited for:

  • Consumer GPUs
  • Quantized CPU inference
  • Embedded or low-resource environments

It offers a strong balance between performance, responsiveness, and efficiency.


Disclaimer

This model is uncensored and designed for research, experimentation, and user-controlled environments. Outputs may include content that would normally be filtered in more restrictive models. Users are responsible for ensuring compliance with applicable laws, policies, and ethical guidelines when deploying or using this model.


Acknowledgements

Special thanks to:

  • The creators and maintainers of the Gemma 3 architecture
  • The open-source community supporting training, fine-tuning, quantization, and deployment tools

README history 8 versions

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

  1. 2026-01-06Update README.md5487c8c3.4 KB
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  8. 2026-01-06initial commitaebed1523 B
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