Meta-Llama-3-8B-Instruct-abliterated-v3
8BLlama
from failspy/Meta-Llama-3-8B-Instruct-abliterated-v3
↓ 371.5K♥ 6923 repos
Llama-3.1-8B-Lexi-Uncensored-V2
Llama-3.1-8B-Lexi-Uncensored-V2 is a abliterated and uncensored variant of Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2, published on Hugging Face by Orenguteng. It is 8B parameters, single consumer GPU class and llama3.1 licence. It is distributed across 33 repositories in GGUF, Transformers, AWQ and GGUF (imatrix) formats, totalling 32.1K downloads.
Specification
- Model name
- Llama-3.1-8B-Lexi-Uncensored-V2
- Source repository
- Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
- Publisher
- Orenguteng
- Parameters
- 8B
- VRAM required
- ~5.6 GB at Q4_K_M, 4k context (estimated) — runs on 6 GB cards
- Hardware class
- 4B – 10B — single consumer GPU
- Licence
- llama3.1
- Task
- Text generation
- Context window
- Not documented
- Ablation scope
- Not stated by the publisher
- Formats available
- GGUF, Transformers, AWQ, GGUF (imatrix), MLX, NVFP4
- First indexed
- 9 Aug 2024
- Last updated
- 31 Oct 2026
Ablation technique
How Llama-3.1-8B-Lexi-Uncensored-V2 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
“Think step by step with a logical reasoning and intellectual sense before you provide any response.”
Running it
Commands are templates — confirm the exact repository and quant file before use.
llama.cpp / GGUF
hf download bartowski/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF --local-dir ./llama-3.1-8b-lexi-uncensored-v2
llama-cli -m ./llama-3.1-8b-lexi-uncensored-v2/<file>.gguf -p "..."Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer
repo = "Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
repo, torch_dtype="auto", device_map="auto"
)vLLM
vllm serve Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2 --trust-remote-codeDownloads and variants (32)
Every published repository of Llama-3.1-8B-Lexi-Uncensored-V2, 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-3.1-8B-Lexi-Uncensored-V2 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 Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2, not added by ablation — at 8B 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 llama3.1, but the terms that bind you are Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2’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 Llama-3.1-8B-Lexi-Uncensored-V2 is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with Orenguteng, and does not independently verify publisher claims. See responsible use.