Llama-3.2-3B-Instruct-uncensored
3BLlamauncensored
from meta-llama/Llama-3.2-3B-Instruct
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Llama-3.2-3B-Instruct-heretic-ablitered-uncensored
Llama-3.2-3B-Instruct-heretic-ablitered-uncensored is a Heretic-ablated variant of meta-llama/Llama-3.2-3B-Instruct, published on Hugging Face by DavidAU. It is 3B parameters and runs on a laptop CPU class. It is distributed across 6 repositories in Transformers, GGUF and GGUF (imatrix) formats, totalling 7.6K downloads.
Specification
- Model name
- Llama-3.2-3B-Instruct-heretic-ablitered-uncensored
- Source repository
- DavidAU/Llama-3.2-3B-Instruct-heretic-ablitered-uncensored
- Base model
- meta-llama/Llama-3.2-3B-Instruct
- Publisher
- DavidAU
- Parameters
- 3B
- VRAM required
- ~2.5 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
- Transformers, GGUF, GGUF (imatrix)
- First indexed
- 21 Nov 2025
- Last updated
- 1 Nov 2026
Ablation technique
How Llama-3.2-3B-Instruct-heretic-ablitered-uncensored was modified, and what that implies.
Heretic
Automated directional ablation via the Heretic toolchain, which searches for the refusal direction and applies it with a KL-divergence budget so general capability is preserved.
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
“Original Model Refusal rate: 96/100”
Running it
Commands are templates — confirm the exact repository and quant file before use.
llama.cpp / GGUF
hf download mradermacher/Llama-3.2-3B-Instruct-heretic-ablitered-uncensored-GGUF --local-dir ./llama-3.2-3b-instruct-heretic-ablitered-uncensored
llama-cli -m ./llama-3.2-3b-instruct-heretic-ablitered-uncensored/<file>.gguf -p "..."Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer
repo = "DavidAU/Llama-3.2-3B-Instruct-heretic-ablitered-uncensored"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
repo, torch_dtype="auto", device_map="auto"
)vLLM
vllm serve DavidAU/Llama-3.2-3B-Instruct-heretic-ablitered-uncensored --trust-remote-codeDownloads and variants (5)
Every published repository of Llama-3.2-3B-Instruct-heretic-ablitered-uncensored, including quantised re-releases by other authors.
| Repository | Format | Downloads |
|---|---|---|
| mradermacher/Llama-3.2-3B-Instruct-heretic-ablitered-uncensored-GGUF | GGUF | 3K |
| tinyopsec/Llama-3.2-3B-Instruct-heretic-ablitered-uncensored-GGUF | GGUF | 2.7K |
| mradermacher/Llama-3.2-3B-Instruct-heretic-ablitered-uncensored-i1-GGUF | GGUF (imatrix) | 1K |
| DavidAU/Llama-3.2-3B-Instruct-heretic-ablitered-uncensoredsource | Transformers | 542 |
| Banany/Llama-3.2-3B-Instruct-heretic-ablitered-uncensored-Q4_K_M-GGUF | GGUF | 306 |
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-heretic-ablitered-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.
- 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-heretic-ablitered-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 DavidAU, and does not independently verify publisher claims. See responsible use.