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

alib97/Josiefied-Qwen3-14B-abliterated-v3-mlx-4Bit

alib97 Qwen 15B 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/alib97%2FJosiefied-Qwen3-14B-abliterated-v3-mlx-4Bit"
Response includes
  • classification m1
  • files 14
  • hub_downloads_all_time 1,260
  • author_summary 1 models
  • readme_text full
10 credits · hourly refresh · ~4 KB payload Get an API key →
Abliteration classifier · v1.0.0
M1
Primary method

Direct removal

No other method signals detected in this model.
Confidence
MEDIUM
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.
  • 'abliterated' in name/tags
  • is_gguf=0 (base model)
  • no specific method indicators - defaulting to M1 (most common)
Refusal direction extracted via
Extraction technique

Difference-of-means

Confidence
MEDIUM
Why we say so
primary_method=M1; difference-of-means is the reference extraction for M1/M3 (Arditi 2024)
Downloads · lifetime
1K
102 last 30d - cooling
Likes
0
Model age
7mo ago
created 2026-02-14
Downloads over time
Now1.3K→from142↑820%
845309771.4K142 on Feb 181.3K on Oct 111.3K on Oct 10FebAprJunAugOct
Feb 18 → Oct 11 · 73 snapshots · spans 235 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
mlx safetensors qwen3 chat mlx-my-repo text-generation conversational base_model:Goekdeniz-Guelmez/Josiefied-Qwen3-14B-abliterated-v3 base_model:quantized:Goekdeniz-Guelmez/Josiefied-Qwen3-14B-abliterated-v3 4-bit region:us

Related

Total size
8.60 GB
Files
14
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-02-14 14:53

Files by quantization

Auxiliary files 14 files 8.61 GB
model-00001-of-00002.safetensors 4.96 GB fb6792d2 download
model-00002-of-00002.safetensors 3.63 GB 84606da1 download
tokenizer.json 10.9 MB aeb13307 download
vocab.json 2.65 MB 4783fe10 download
merges.txt 1.59 MB 31349551 download
model.safetensors.index.json 84.3 KB ba8ed6f4 download
tokenizer_config.json 5.28 KB ddaf6980 download
chat_template.jinja 4.02 KB 699ff8df download
.gitattributes 1.53 KB 52373fe2 download
README.md 1.01 KB df98a834 download
config.json 990 B bd6d7d27 download
added_tokens.json 707 B b54f9135 download
special_tokens_map.json 613 B ac23c0aa download
generation_config.json 214 B e4f1d319 download

README current version from Hugging Face


tags:

  • chat
  • mlx
  • mlx-my-repo
    base_model: Goekdeniz-Guelmez/Josiefied-Qwen3-14B-abliterated-v3
    pipeline_tag: text-generation

alib97/Josiefied-Qwen3-14B-abliterated-v3-mlx-4Bit

The Model alib97/Josiefied-Qwen3-14B-abliterated-v3-mlx-4Bit was converted to MLX format from Goekdeniz-Guelmez/Josiefied-Qwen3-14B-abliterated-v3 using mlx-lm version 0.29.1.

Use with mlx

pip install mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("alib97/Josiefied-Qwen3-14B-abliterated-v3-mlx-4Bit")

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)

README history 1 version

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

  1. 2026-02-14Upload README.md with huggingface_hubb7718361 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