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AtomicChat/LFM3-1.7B-Uncensored-GGUF

AtomicChat 1.7B GGUF
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  • classification m-uncensored
  • files 5
  • author_summary 24 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 · 30-day
0
Likes
5
Model age
today
created 2026-10-27

Genealogy 0 direct forks

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Metadata

License
other
Languages
en zh de
Quantizations
Q4_K Q6_K
Tags
gguf quantized lfm3 text-generation en zh de base_model:LiquidAI/LFM3-1.7B base_model:quantized:LiquidAI/LFM3-1.7B license:other endpoints_compatible region:us

Related

Total size
2.53 GB
Files
5
Quantizations
3
Registered
2026-10-27 21:01
Last updated on HF
2026-10-27 20:38

Files by quantization

Q6_K 1 file 1.48 GB
LFM3-1.7B-Uncensored-AD-Q6_K.gguf 1.48 GB 4a7d91c0 download
Q4_K 1 file 1.05 GB
LFM3-1.7B-Uncensored-AD-Q4_K_M.gguf 1.05 GB b22df656 download
Auxiliary files 3 files 13.8 KB
LICENSE 10.3 KB 25e731c6 download
.gitattributes 1.85 KB d8354922 download
README.md 1.63 KB 425c91d5 download

README current version from Hugging Face


base_model: LiquidAI/LFM3-1.7B
license: other
license_name: lfm-open-license-v1.0
license_link: https://huggingface.co/LiquidAI/LFM3-1.7B/blob/main/LICENSE
language:

  • en
  • zh
  • de
    pipeline_tag: text-generation
    library_name: gguf
    tags:
  • gguf
  • quantized
  • lfm3

LFM3-1.7B Uncensored — GGUF (by AtomicChat)

Safety-ablated GGUF of LiquidAI/LFM3-1.7B. A projected rank-1 LoRA (direction = mean harmful − mean harmless activations, with the harmless component projected out) is baked into the weights at W*=2.0, then AD-quantized.

What changed (measured)

metric base uncensored
refusals on harmful prompts 61.7% 0.0%
false refusals (XSTest) 5.2% 0.0%
MMLU (2000 q) 41.0% 41.0% (McNemar p=1.0 — no drop)
needle (long context) 3/3 3/3
ΔKLD vs base (neutral) — +0.019

A random edit of the same size dropped MMLU 1.3pp and had a larger ΔKLD (0.028), so the targeted direction is both more effective and less damaging. Thinking-loop and empty-output checks pass at W*=2.0.

Rungs

Rung GB on disk bpw
AD-Q6_K 1.6 7.31
AD-Q4_K_M 1.1 5.20

Run (llama.cpp)

Needs a build with LFM3 support (merged in llama.cpp #31252; produced at llama.cpp 19cce69).

llama-cli -hf AtomicChat/LFM3-1.7B-Uncensored-GGUF:AD-Q4_K_M -p "Hello"

Base model & license

Base model: LiquidAI/LFM3-1.7B. License: LFM Open License v1.0 (see LICENSE). This removes safety refusals; use responsibly and in line with the base license.

Quants by AtomicChat.

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