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

alexgusevski/Llama-3.2-8X3B-MOE-Dark-Champion-Instruct-uncensored-abliterated-18.4B-mlx-fp16

alexgusevski Llama 18B MoE second-order
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/alexgusevski%2FLlama-3.2-8X3B-MOE-Dark-Champion-Instruct-uncensored-abliterated-18.4B-mlx-fp16"
Response includes
  • classification m5-frankenstein
  • files 16
  • hub_downloads_all_time 1,594
  • author_summary 64 models
  • readme_text full
10 credits · hourly refresh · ~4 KB payload Get an API key →
Abliteration classifier · v1.0.0
M5-F
Primary method

Frankenstein's creature

Applied on top of direct removal inherited from the base model.
Confidence
MEDIUM
Inherited from base model
Why this label 3 signals
Method inferred from partial signals - repository name, related files, or tag patterns. Producer identity not confirmed; label may sharpen or shift as we gather more evidence.
  • merge tag / mergekit / dare-ties present
  • name suggests non-standard architecture combination (MoE / frankenmerge / NxNB pattern)
  • abliterated marker present
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
2K
82 last 30d - cooling
Likes
0
Model age
8mo ago
created 2026-01-15
Downloads over time
Now1.6K→from151↑979%
776441.2K1.8K151 on Jan 141.6K on Oct 11JanMarMayJulSep
Jan 14 → Oct 11 · 78 snapshots · spans 270 days

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

Tags
transformers safetensors mixtral text-generation mergekit merge llama-3 llama-3.2 mlx mlx-my-repo conversational base_model:DavidAU/Llama-3.2-8X3B-MOE-Dark-Champion-Instruct-uncensored-abliterated-18.4B

Related

Total size
34.3 GB
Files
16
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-01-16 16:37

Files by quantization

Auxiliary files 16 files 34.3 GB
model-00004-of-00008.safetensors 4.69 GB f012011f download
model-00006-of-00008.safetensors 4.69 GB 453b76b3 download
model-00007-of-00008.safetensors 4.69 GB 7704e125 download
model-00005-of-00008.safetensors 4.69 GB acdd1079 download
model-00002-of-00008.safetensors 4.69 GB b58b206d download
model-00003-of-00008.safetensors 4.69 GB ccb6e53b download
model-00001-of-00008.safetensors 4.67 GB cda7e51b download
model-00008-of-00008.safetensors 1.48 GB cd7e648e download
tokenizer.json 16.4 MB 65ff5472 download
tokenizer_config.json 49.5 KB e7244d34 download
model.safetensors.index.json 26.0 KB 11939e1d download
chat_template.jinja 3.74 KB 1bad6a0f download
.gitattributes 1.53 KB 52373fe2 download
README.md 1.41 KB f4564fdc download
config.json 1.13 KB d0e68c9c download
special_tokens_map.json 446 B 4dd5e992 download

README current version from Hugging Face


library_name: transformers
tags:

  • mergekit
  • merge
  • llama-3
  • llama-3.2
  • mlx
  • mlx-my-repo
    base_model: DavidAU/Llama-3.2-8X3B-MOE-Dark-Champion-Instruct-uncensored-abliterated-18.4B

alexgusevski/Llama-3.2-8X3B-MOE-Dark-Champion-Instruct-uncensored-abliterated-18.4B-mlx-fp16

The Model alexgusevski/Llama-3.2-8X3B-MOE-Dark-Champion-Instruct-uncensored-abliterated-18.4B-mlx-fp16 was converted to MLX format from DavidAU/Llama-3.2-8X3B-MOE-Dark-Champion-Instruct-uncensored-abliterated-18.4B using mlx-lm version 0.29.1.

Use with mlx

pip install mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("alexgusevski/Llama-3.2-8X3B-MOE-Dark-Champion-Instruct-uncensored-abliterated-18.4B-mlx-fp16")

prompt="hello"

if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, tokenize=False, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Also, if you're interested in large scale AI deployments, read my PlanetaryLabour manifesto on https://planetarylabour.com

README history 2 versions

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

  1. 2026-01-16Update README.md98afeb91.4 KB
    Loading...
  2. 2026-01-15Upload README.md with huggingface_hubc9b22821.3 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