⌦abliteratedmodels.org

llama-3.2-1b-abliterated

llama-3.2-1b-abliterated is a refusal-ablated variant of ElementMerc/llama-3.2-1b-uncensored, published on Hugging Face by hasanyt. It is 1B parameters and runs on a laptop CPU class. It is distributed across 4 repositories in GGUF, GGUF (imatrix) and Transformers formats, totalling 5.1K downloads.

Abliteration (directional ablation)1BLlamaUnder 4B↓ 5,148♥ 1

Specification

Model name
llama-3.2-1b-abliterated
Publisher
hasanyt
Parameters
1B
VRAM required
~1.3 GB at Q4_K_M, 4k context (estimated) — runs on 4 GB cards
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
GGUF, GGUF (imatrix), Transformers
First indexed
28 Jul 2026
Last updated
13 Oct 2026

Ablation technique

How llama-3.2-1b-abliterated was modified, and what that implies.

Abliteration (directional ablation)

The single residual-stream direction that mediates refusal is identified from harmful/harmless prompt pairs and projected out of the model weights.

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 is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.”

Running it

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

llama.cpp / GGUF
hf download mradermacher/llama-3.2-1b-abliterated-i1-GGUF --local-dir ./llama-3.2-1b-abliterated
llama-cli -m ./llama-3.2-1b-abliterated/<file>.gguf -p "..."
Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer

repo = "hasanyt/llama-3.2-1b-abliterated"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
    repo, torch_dtype="auto", device_map="auto"
)
vLLM
vllm serve hasanyt/llama-3.2-1b-abliterated --trust-remote-code

Downloads and variants (3)

Every published repository of llama-3.2-1b-abliterated, including quantised re-releases by other authors.

Security-team assessment

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

  • llama-3.2-1b-abliterated 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 ElementMerc/llama-3.2-1b-uncensored, not added by ablation — at 1B 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.
  • 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-3.2-1b-abliterated is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with hasanyt, and does not independently verify publisher claims. See responsible use.