LFM2.5-2.6B-Uncensored
2.6BOtheruncensored
from LiquidAI/LFM2.5-2.6B
↓ 17.3K♥ 178 repos
LFM2.5-VL-3B-Uncensored
LFM2.5-VL-3B-Uncensored is a abliterated and uncensored variant of LiquidAI/LFM2.5-VL-3B, published on Hugging Face by SC117. It is 3B parameters, runs on a laptop CPU class and other licence. It is distributed across 2 repositories in GGUF format, totalling 7.6K downloads.
Specification
- Model name
- LFM2.5-VL-3B-Uncensored
- Source repository
- SC117/LFM2.5-VL-3B-Uncensored-GGUF
- Base model
- LiquidAI/LFM2.5-VL-3B
- Publisher
- SC117
- Parameters
- 3B
- Hardware class
- Under 4B — runs on a laptop CPU
- Licence
- other
- Task
- Image text to text
- Context window
- 128K tokens (as documented)
- Ablation scope
- Not stated by the publisher
- Formats available
- GGUF
- First indexed
- 13 Aug 2026
- Last updated
- 13 Aug 2026
Ablation technique
How LFM2.5-VL-3B-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
“LFM2.5-VL-3B is Liquid AI's official 3.1B vision-language edge model: the LFM2.5-2.6B hybrid language backbone (30 layers: 22 double-gated short-convolution blocks + 8 GQA, 128K context, 128K vocab) paired with a SigLIP2 NaFlex vision encoder (256×256, patch 16) and a language-aligned projector. This release merges...”
Running it
Commands are templates — confirm the exact repository and quant file before use.
llama.cpp / GGUF
hf download SC117/LFM2.5-VL-3B-Uncensored-GGUF --local-dir ./lfm2.5-vl-3b-uncensored
llama-cli -m ./lfm2.5-vl-3b-uncensored/<file>.gguf -p "..."Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer
repo = "SC117/LFM2.5-VL-3B-Uncensored-GGUF"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
repo, torch_dtype="auto", device_map="auto"
)vLLM
vllm serve SC117/LFM2.5-VL-3B-Uncensored-GGUF --trust-remote-codeDownloads and variants (1)
The only published repository of LFM2.5-VL-3B-Uncensored.
| Repository | Format | Downloads |
|---|---|---|
| SC117/LFM2.5-VL-3B-Uncensored-GGUFsource | GGUF | 7.6K |
Security-team assessment
Derived from this model’s metadata and the publisher’s claims — not from benchmarks run by this site.
- LFM2.5-VL-3B-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 LiquidAI/LFM2.5-VL-3B, 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.
- Declared licence is other, but the terms that bind you are LiquidAI/LFM2.5-VL-3B’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 LFM2.5-VL-3B-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 SC117, and does not independently verify publisher claims. See responsible use.