language:
- en
license: apache-2.0
library_name: mlx
pipeline_tag: image-text-to-text
base_model: philbert440/Qwen3.8-27B-Uncensored-Cyber
tags: - mlx
- qwen3_5
- qwen3.8
- 8-bit
- uncensored
- abliterated
- cyber
Qwen3.8-27B-Uncensored-Cyber-MLX-8bit
Unofficial 8-bit MLX conversion ofphilbert440/Qwen3.8-27B-Uncensored-Cyber
for Apple Silicon.
The source is a cyber-specialized, substantially de-refused derivative ofQwen/Qwen3.8-27B. This repository is only a format conversion and
quantization; it does not claim additional training or safety evaluation.
Conversion
| Property | Value |
|---|---|
| Source revision | c3e40d890c50b5ad5e7cb035701316605a7f6d16 |
| Converter | mlx-lm 0.31.3 |
| Quantization | MLX affine, 8 bits, group size 64 |
| Reported average | 8.501 bits per weight |
| Unquantized dtype | BF16 |
| Architecture | Qwen3_5ForConditionalGeneration |
Conversion command:
mlx_lm.convert \
--hf-path /path/to/pinned-source-snapshot \
--mlx-path ./Qwen3.8-27B-Uncensored-Cyber-MLX-8bit \
--quantize \
--q-bits 8 \
--q-group-size 64
Usage
pip install "mlx-lm==0.31.3"
mlx_lm.generate \
--model rwcii/Qwen3.8-27B-Uncensored-Cyber-MLX-8bit \
--prompt "Explain the purpose of network segmentation." \
--max-tokens 256
OpenAI-compatible local server:
mlx_lm.server \
--model rwcii/Qwen3.8-27B-Uncensored-Cyber-MLX-8bit \
--host 127.0.0.1 \
--port 8080
Local validation
Validated on Apple Silicon with MLX-LM 0.31.3:
- Model load and text generation succeeded.
- OpenAI-compatible chat completion succeeded.
- Structured function/tool calling produced valid OpenAI-format JSON.
- Observed generation throughput was approximately 16.7 tokens/second for
one short test, with approximately 28.9 GB peak memory. These figures are
machine- and workload-specific and are not a general benchmark.
See CHECKSUMS.sha256 for artifact hashes.
Safety and limitations
The source model has had safety alignment deliberately reduced and is tuned
to answer cyber and offensive-security questions that other models may
refuse. It can generate harmful, illegal, incorrect, or dangerous material.
It has no meaningful built-in safety boundary.
Use only in environments where authorization, access control, monitoring,
and applicable-law compliance are independently enforced. Do not treat the
model as an authority, execute generated commands without review, or expose
it directly to untrusted users. The uploader provides no warranty and has
not independently reproduced the source author's behavioral evaluations.
Quantization can reduce accuracy, reasoning quality, and tool-call
reliability. Validation above was limited and is not a comprehensive safety,
quality, multimodal, or cybersecurity benchmark.
Attribution and license
- Base model:
Qwen/Qwen3.8-27B - Cyber derivative:
philbert440/Qwen3.8-27B-Uncensored-Cyber - MLX conversion:
rwcii
Distributed under the Apache License 2.0 inherited from the source. This is
an unofficial community conversion and is not affiliated with or endorsed by
Qwen, Alibaba Cloud, Philbert440, Hugging Face, Apple, or the MLX team.