abliteratedmodels.org

Llama-3.2-3B-Instruct-uncensored

Llama-3.2-3B-Instruct-uncensored is a abliterated and uncensored variant of meta-llama/Llama-3.2-3B-Instruct, published on Hugging Face by chuanli11. It is 3B parameters and runs on a laptop CPU class. It is distributed across 47 repositories in Transformers, GGUF, GGUF (imatrix) and OpenVINO formats, totalling 65.8K downloads.

Abliteration + uncensored fine-tune3BLlamaUnder 4B65,762153

Specification

Model name
Llama-3.2-3B-Instruct-uncensored
Publisher
chuanli11
Parameters
3B
Hardware class
Under 4B — runs on a laptop CPU
Licence
Not declared
Task
Text generation
Context window
Not documented
Ablation scope
Not stated by the publisher
Formats available
Transformers, GGUF, GGUF (imatrix), OpenVINO, MLX
First indexed
27 Sept 2024
Last updated
20 Aug 2026

Ablation technique

How Llama-3.2-3B-Instruct-uncensored was modified, and what that implies.

Abliteration + uncensored fine-tune

Directional ablation combined with additional fine-tuning on unfiltered data, so behaviour diverges from the base model beyond refusal removal alone.

Reported scope: Not stated by the publisher. Publishers frequently omit this, so verify behaviour empirically rather than assuming full coverage.

From the publisher’s model card

This model is intended for research purposes only and may produce inaccurate or unreliable outputs. Use it cautiously and at your own risk.

Running it

Commands are templates — confirm the exact repository and quant file before use.

llama.cpp / GGUF
hf download bartowski/Llama-3.2-3B-Instruct-uncensored-GGUF --local-dir ./llama-3.2-3b-instruct-uncensored
llama-cli -m ./llama-3.2-3b-instruct-uncensored/<file>.gguf -p "..."
Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer

repo = "chuanli11/Llama-3.2-3B-Instruct-uncensored"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
    repo, torch_dtype="auto", device_map="auto"
)
vLLM
vllm serve chuanli11/Llama-3.2-3B-Instruct-uncensored --trust-remote-code

Downloads and variants (46)

Every published repository of Llama-3.2-3B-Instruct-uncensored, including quantised re-releases by other authors.

RepositoryFormatDownloads
bartowski/Llama-3.2-3B-Instruct-uncensored-GGUFGGUF51.2K
mradermacher/Llama-3.2-3B-Instruct-uncensored-GGUFGGUF4.6K
mradermacher/Llama-3.2-3B-Instruct-uncensored-i1-GGUFGGUF (imatrix)2.3K
MaziyarPanahi/Llama-3.2-3B-Instruct-uncensored-GGUFGGUF1.7K
chuanli11/Llama-3.2-3B-Instruct-uncensoredsourceTransformers1.1K
brittlewis12/Llama-3.2-3B-Instruct-uncensored-GGUFGGUF870
mlx-community/Llama-3.2-3B-Instruct-uncensored-6bitMLX633
QuantFactory/Llama-3.2-3B-Instruct-uncensored-GGUFGGUF581
tostideluxekaas/Llama-3.2-3B-Instruct-uncensored-GGUFGGUF363
Abc7347/Llama-3.2-3B-Instruct-uncensored-Q4_K_M-GGUFGGUF275
second-state/Llama-3.2-3B-Instruct-Uncensored-GGUFGGUF249
X3NO/Llama-3.2-3B-Instruct-uncensored-Q5_K_M-GGUFGGUF247
tensorblock/Llama-3.2-3B-Instruct-uncensored-GGUFGGUF165
matrixportalx/Llama-3.2-3B-Instruct-uncensored-Q3_K_M-GGUFGGUF162
Jadzblaze99/Llama-3.2-3B-Instruct-uncensored-GGUFGGUF139
Ether4o4/Llama-3.2-3B-Instruct-uncensored-GGUFGGUF132
roleplaiapp/Llama-3.2-3B-Instruct-uncensored-Q6_K-GGUFGGUF128
nash111/Llama-3.2-3B-Instruct-uncensored-Q4_K_M-GGUFGGUF88
v8karlo/Llama-3.2-3B-Instruct-uncensored-Q8_0-GGUFGGUF73
gaianet/Llama-3.2-3B-Instruct-Uncensored-GGUFGGUF70
matrixportalx/Llama-3.2-3B-Instruct-uncensored-Q4_K_M-GGUFGGUF56
Bradarr/Llama-3.2-3B-Instruct-uncensored-Q4_K_M-GGUFGGUF46
nolynn/Llama-3.2-3B-Instruct-uncensored-Q6_K-GGUFGGUF39
Atmpushout/Llama-3.2-3B-Instruct-uncensored-GGUFGGUF39
X3NO/Llama-3.2-3B-Instruct-uncensored-Q4_K_M-GGUFGGUF37
tostideluxekaas/Llama-3.2-3B-Instruct-uncensoredTransformers36
goodasdgood/Llama-3.2-3B-Instruct-uncensored-Q2_K-GGUFGGUF36
nolynn/Llama-3.2-3B-Instruct-uncensored-Q5_K_S-GGUFGGUF34
knoveleng/Llama-3.2-3B-Instruct-UncensoredTransformers32
prajwal-ibm/Llama-3.2-3B-Instruct-uncensored-f16GGUF32
Plus 16 further repositories with fewer downloads, all counted in the totals above.

Security-team assessment

Derived from this model’s metadata and the publisher’s claims — not from benchmarks run by this site.

  • Llama-3.2-3B-Instruct-uncensored will attempt offensive-security prompts that a hosted commercial model declines, which is what makes it usable for red-team corpus generation and for measuring what an unaligned model of this class produces.
  • Capability is inherited from meta-llama/Llama-3.2-3B-Instruct, not added by ablation — at 3B parameters, expect a small model’s reasoning and a high error rate on exploit detail.
  • The publisher does not state which layers were ablated, so assume nothing about refusal consistency — probe it directly.
  • This release adds fine-tuning on unfiltered data, so its behaviour diverges from the base model beyond refusal removal — differences you measure cannot be attributed to ablation alone.
  • No licence is declared on this repository, which is a compliance problem in itself. Resolve it against the base model’s terms before use.

Handling: run it isolated, put moderation in front of it if anyone outside your team can reach it, and verify the weights before loading — these are third-party artifacts. Full handling and licence guidance.

Metadata for Llama-3.2-3B-Instruct-uncensored is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with chuanli11, and does not independently verify publisher claims. See responsible use.