license: apache-2.0
library_name: mlx
base_model: treadon/granite-4.1-8b-Abliterated-AND-Disinhibited
tags:

• abliteration
• disinhibition
• granite
• mechanistic-interpretability
• mlx
  pipeline_tag: text-generation

granite-4.1-8b-Abliterated-AND-Disinhibited-mxfp8-mlx

Brainwaves

         arc   arc/e boolq hswag obkqa piqa  wino
mxfp8    0.496,0.692,0.864,0.666,0.466,0.770,0.632

Quant    Perplexity      Peak Memory   Tokens/sec
mxfp8    9.518 ± 0.094   11.75 GB      686

Original model

granite-4.1-8b
mxfp8    0.486,0.666,0.875,0.636,0.450,0.766,0.631

Quant    Perplexity      Peak Memory   Tokens/sec
mxfp8   10.134 ± 0.107   12.17 GB      668

This model granite-4.1-8b-Abliterated-AND-Disinhibited-mxfp8-mlx was
converted to MLX format from treadon/granite-4.1-8b-Abliterated-AND-Disinhibited
using mlx-lm version 0.31.3.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("granite-4.1-8b-Abliterated-AND-Disinhibited-mxfp8-mlx")

prompt = "hello"

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

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