license: apache-2.0 base_model: AEON-7/Qwen3.8-27B-AEON-ULTIMATE-UNCENSORED-BF16 language:

en
zh
multilingual library_name: transformers pipeline_tag: text-generation tags:
27b
abliterated
abliterix
aeon
aeon-7
bf16
bfloat16
chat
coding
conversational
function-calling
gated-deltanet
gdn
hybrid-attention
instruct
multimodal
qwen
qwen3
qwen3.8
reasoning
refusal-removed
thinking
tool-calling
uncensored
unfiltered
vision
vision-language
vllm
mlx
mlx-my-repo

Fmuaddib/Qwen3.8-27B-AEON-ULTIMATE-UNCENSORED-BF16-mlx-8Bit

The Model Fmuaddib/Qwen3.8-27B-AEON-ULTIMATE-UNCENSORED-BF16-mlx-8Bit was converted to MLX format from AEON-7/Qwen3.8-27B-AEON-ULTIMATE-UNCENSORED-BF16 using mlx-lm version 0.31.2.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("Fmuaddib/Qwen3.8-27B-AEON-ULTIMATE-UNCENSORED-BF16-mlx-8Bit")

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)

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate model, tokenizer = load("Fmuaddib/Qwen3.8-27B-AEON-ULTIMATE-UNCENSORED-BF16-mlx-8Bit") 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)