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lfm3-vl-2b-heretic

lfm3-vl-2b-heretic is a Heretic-ablated variant of LiquidAI/LFM3-VL-2B, published on Hugging Face by Lucasgitguy-co. It is 2B parameters, runs on a laptop CPU class and other licence. It is distributed across 6 repositories in GGUF, Transformers and MLX formats, totalling 7.1K downloads.

Heretic2BOtherUnder 4B↓ 7,089♥ 4

Specification

Model name
lfm3-vl-2b-heretic
Parameters
2B
VRAM required
~1.9 GB at Q4_K_M, 4k context (estimated) — runs on 4 GB cards
Hardware class
Under 4B — runs on a laptop CPU
Licence
other
Task
Image text to text
Context window
Not documented
Ablation scope
Not stated by the publisher
Formats available
GGUF, Transformers, MLX
First indexed
28 Oct 2026
Last updated
2 Nov 2026

Ablation technique

How lfm3-vl-2b-heretic 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

“LFM3-VL-2B Heretic checkpoint in Hugging Face Safetensors format, with a language model, vision encoder, projector, tokenizer, processor configuration, and custom model code.”

Running it

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

llama.cpp / GGUF
hf download saidutta69/LFM3-VL-2B-heretic --local-dir ./lfm3-vl-2b-heretic
llama-cli -m ./lfm3-vl-2b-heretic/<file>.gguf -p "..."
Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer

repo = "Lucasgitguy-co/lfm3-vl-2b-heretic"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
    repo, torch_dtype="auto", device_map="auto"
)
vLLM
vllm serve Lucasgitguy-co/lfm3-vl-2b-heretic --trust-remote-code

Downloads and variants (5)

Every published repository of lfm3-vl-2b-heretic, 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.

  • lfm3-vl-2b-heretic 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 LiquidAI/LFM3-VL-2B, not added by ablation — at 2B 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.
  • Declared licence is other, but the terms that bind you are LiquidAI/LFM3-VL-2B’s — a re-release cannot grant more than its parent.

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 lfm3-vl-2b-heretic is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with Lucasgitguy-co, and does not independently verify publisher claims. See responsible use.