← back to catalog · registered 2026-08-22 13:56

goodasdgood/Llama-3.1-8B-Lexi-Uncensored-V2-Q8_0-GGUF

goodasdgood Llama 8B GGUF second-order 131K ctx
Your rig guess connected
? Why do I need an app?
Reading your rig…

This is a rough estimate. Install the free app - we'll show exact numbers.

Reading real hardware from your app right now. Numbers below are exact.

Below is the per-quantization compatibility for this model.

curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/goodasdgood%2FLlama-3.1-8B-Lexi-Uncensored-V2-Q8_0-GGUF"
Response includes
  • classification m-uncensored
  • files 3
  • benchmarks 16 entries
  • hub_downloads_all_time 1,420
  • author_summary 3 models
  • readme_text full
10 credits · hourly refresh · ~4 KB payload Get an API key →
Abliteration classifier · v1.0.0
M-U
Primary method

Uncensored (method unknown)

No other method signals detected in this model.
Confidence
LOW
Why this label 3 signals
Weak or ambiguous signals. Best guess based on catalog patterns; treat as tentative and check the evidence below.
  • 'uncensored' in name/tags but no 'abliterated' marker
  • method not identifiable from author declaration alone
  • may be DPO fine-tune, prompt engineering, or unknown technique
Refusal direction extraction

No specific extraction method could be identified for this model. The producer either did not document it or used a proprietary pipeline.

What is a refusal direction? →
Downloads · lifetime
1K
125 last 30d - cooling
Likes
2
Model age
2.1y ago
created 2024-08-25
Downloads over time
Now1.5K→from99↑1,381%
05371.1K1.6K99 on Aug 21, 20241.5K on Oct 12Aug '24Dec '24Apr '25Aug '25Dec '25AprAug
Aug 21, 2024 → Oct 12 · 152 snapshots · spans 782 days

Benchmarks

Benchmark Score Source
BBH average 0.46037099494097816 OpenLLM-v2
IFEval instruct 0.8189448441247003 OpenLLM-v2
IFEval-Prompt 0.7393715341959335 OpenLLM-v2
MATH lvl 5 0.1691842900302115 OpenLLM-v2
MMLU-Pro 0.3780751329787234 OpenLLM-v2
Entertainment 0.7 UGI
Hazardous 0 UGI
Natural Intelligence 16.16 UGI
Political lean -21.7% UGI
Sensitive-Info 7.32 UGI
SocPol 1.3 UGI
UGI 25.72 UGI
Willingness (10) 6.2 UGI
W10-Adherence 6.5 UGI
W10-Direct 6 UGI
Writing 19.4 UGI

Genealogy 0 direct forks

Full fork graph →

This model's place in the market. Above: what it was derived from. Below: the tree of everything derived from it.

Metadata

License
llama3.1
Tags
gguf llama-cpp gguf-my-repo base_model:Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2 base_model:quantized:Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2 license:llama3.1 endpoints_compatible region:us conversational

Related

Total size
7.95 GB
Files
3
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2024-08-25 15:50

Files by quantization

Auxiliary files 3 files 7.95 GB
llama-3.1-8b-lexi-uncensored-v2-q8_0.gguf 7.95 GB 20ee1846 download
README.md 1.90 KB 481b1c15 download
.gitattributes 1.56 KB 72aca53d download

README current version from Hugging Face


base_model: Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
license: llama3.1
tags:

  • llama-cpp
  • gguf-my-repo

goodasdgood/Llama-3.1-8B-Lexi-Uncensored-V2-Q8_0-GGUF

This model was converted to GGUF format from Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2 using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.

Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo goodasdgood/Llama-3.1-8B-Lexi-Uncensored-V2-Q8_0-GGUF --hf-file llama-3.1-8b-lexi-uncensored-v2-q8_0.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo goodasdgood/Llama-3.1-8B-Lexi-Uncensored-V2-Q8_0-GGUF --hf-file llama-3.1-8b-lexi-uncensored-v2-q8_0.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.

git clone https://github.com/ggerganov/llama.cpp

Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).

cd llama.cpp && LLAMA_CURL=1 make

Step 3: Run inference through the main binary.

./llama-cli --hf-repo goodasdgood/Llama-3.1-8B-Lexi-Uncensored-V2-Q8_0-GGUF --hf-file llama-3.1-8b-lexi-uncensored-v2-q8_0.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo goodasdgood/Llama-3.1-8B-Lexi-Uncensored-V2-Q8_0-GGUF --hf-file llama-3.1-8b-lexi-uncensored-v2-q8_0.gguf -c 2048

README history 1 version

The author's README evolved over time. Click a version to see its content at that point.

  1. 2024-08-25Upload README.md with huggingface_hubd0aff531.9 KB
    Loading...
Catalog is the map. Apps are the tools.

Run models on your own machine, not in the cloud.

Every model page has an "Open in Abliteration" button that hands the model directly to the first-party desktop client, at the quantization your rig can actually run. No API keys, no subscription, no prompt leakage.

Open in Abliteration