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tensorblock/gemma-3-1b-it-abliterated-GGUF

tensorblock Gemma 1B GGUF second-order 33K ctx
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Response includes
  • classification m8
  • files 4
  • hub_downloads_all_time 3,200
  • author_summary 96 models
  • readme_text full
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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
HIGH
Inherited from base model
Why this label 3 signals
Producer identity confirmed by naming conventions, tags or the model card. This label is very unlikely to change.
  • author=tensorblock (M8 quantization producer)
  • is_gguf=1
  • base_model='huihui-ai/gemma-3-1b-it-abliterated' looks abliterated -> assume M1
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
3K
202 last 30d - cooling
Likes
1
Model age
18mo ago
created 2025-03-21
Downloads over time
Now3.2K→from257↑1,153%
1091.2K2.4K3.5K257 on Mar 19, 20253.2K on Oct 113.2K on Oct 9Mar '25Jun '25Sep '25Dec '25MarJunSep
Mar 19, 2025 → Oct 11 · 121 snapshots · spans 571 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
Quantizations
Q2_K Q3_K
Tags
transformers gguf chat abliterated uncensored TensorBlock GGUF text-generation base_model:huihui-ai/gemma-3-1b-it-abliterated base_model:quantized:huihui-ai/gemma-3-1b-it-abliterated license:gemma endpoints_compatible

Related

Total size
1.32 GB
Files
4
Quantizations
3
Registered
2026-08-22 13:56
Last updated on HF
2026-01-27 21:15

Files by quantization

Q3_K 1 file 689 MB
gemma-3-1b-it-abliterated-Q3_K_M.gguf 689 MB 8b25642d download
Q2_K 1 file 658 MB
gemma-3-1b-it-abliterated-Q2_K.gguf 658 MB b294a744 download
Auxiliary files 2 files 9.49 KB
README.md 7.15 KB c2093686 download
.gitattributes 2.34 KB c23eac21 download

README current version from Hugging Face


license: gemma
library_name: transformers
pipeline_tag: text-generation
extra_gated_heading: Access Gemma on Hugging Face
extra_gated_prompt: To access Gemma on Hugging Face, you’re required to review and
agree to Google’s usage license. To do this, please ensure you’re logged in to Hugging
Face and click below. Requests are processed immediately.
extra_gated_button_content: Acknowledge license
base_model: huihui-ai/gemma-3-1b-it-abliterated
tags:

  • chat
  • abliterated
  • uncensored
  • TensorBlock
  • GGUF

TensorBlock

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huihui-ai/gemma-3-1b-it-abliterated - GGUF

This repo contains GGUF format model files for huihui-ai/gemma-3-1b-it-abliterated.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4882.

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## Prompt template
<bos><start_of_turn>user
{system_prompt}

{prompt}<end_of_turn>
<start_of_turn>model

Model file specification

Filename Quant type File Size Description
gemma-3-1b-it-abliterated-Q2_K.gguf Q2_K 0.690 GB smallest, significant quality loss - not recommended for most purposes
gemma-3-1b-it-abliterated-Q3_K_S.gguf Q3_K_S 0.689 GB very small, high quality loss
gemma-3-1b-it-abliterated-Q3_K_M.gguf Q3_K_M 0.722 GB very small, high quality loss
gemma-3-1b-it-abliterated-Q3_K_L.gguf Q3_K_L 0.752 GB small, substantial quality loss
gemma-3-1b-it-abliterated-Q4_0.gguf Q4_0 0.720 GB legacy; small, very high quality loss - prefer using Q3_K_M
gemma-3-1b-it-abliterated-Q4_K_S.gguf Q4_K_S 0.781 GB small, greater quality loss
gemma-3-1b-it-abliterated-Q4_K_M.gguf Q4_K_M 0.806 GB medium, balanced quality - recommended
gemma-3-1b-it-abliterated-Q5_0.gguf Q5_0 0.808 GB legacy; medium, balanced quality - prefer using Q4_K_M
gemma-3-1b-it-abliterated-Q5_K_S.gguf Q5_K_S 0.836 GB large, low quality loss - recommended
gemma-3-1b-it-abliterated-Q5_K_M.gguf Q5_K_M 0.851 GB large, very low quality loss - recommended
gemma-3-1b-it-abliterated-Q6_K.gguf Q6_K 1.012 GB very large, extremely low quality loss
gemma-3-1b-it-abliterated-Q8_0.gguf Q8_0 1.069 GB very large, extremely low quality loss - not recommended

Downloading instruction

Command line

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

huggingface-cli download tensorblock/gemma-3-1b-it-abliterated-GGUF --include "gemma-3-1b-it-abliterated-Q2_K.gguf" --local-dir MY_LOCAL_DIR

If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:

huggingface-cli download tensorblock/gemma-3-1b-it-abliterated-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'

README history 4 versions

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

  1. 2025-07-09Update README.md8a6f4fe7.2 KB
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  2. 2025-06-19Update README.md19e71c16.4 KB
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  3. 2025-04-21Update README.mdff083056.3 KB
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  4. 2025-03-21Upload folder using huggingface_hub09fb2ce5.4 KB
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