NEXUS-Security-MLX-bf16 – AI Model by ahmedandaloes | AlphaNeural AI

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ahmedandaloes/
NEXUS-Security-MLX-bf16

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offensive-security

text-generation

fableforge-ai/NEXUS-Security

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NEXUS-Security — MLX bf16

Full-precision (bf16) MLX build of fableforge-ai/NEXUS-Security (Qwen2ForCausalLM, ~1.5B), for fast local inference on Apple Silicon.

Precision: bf16 — no quantization, identical weights to source.
Size: ~3 GB · retention: 100% (full precision)
Converted with: mlx-lm, mlx.

Weights unchanged from the source — format + precision conversion only.

Other builds

Build	Bits	Size
MLX-4bit	4	~0.9 GB
MLX-6bit	6	~1.3 GB
MLX-8bit	8	~1.7 GB
MLX-bf16	bf16	~3 GB

GGUF builds (llama.cpp/Ollama): King3Djbl/nexus-security-GGUF.

Usage

pip install mlx-lm

python

from mlx_lm import load, generate
model, tok = load("ahmedandaloes/NEXUS-Security-MLX-bf16")
msgs=[{"role":"user","content":"Name one common web vulnerability."}]
p=tok.apply_chat_template(msgs, add_generation_prompt=True)
print(generate(model, tok, prompt=p, max_tokens=256, verbose=True))

Attribution & license

Source: fableforge-ai/NEXUS-Security · base Qwen/Qwen2-1.5B
License Apache-2.0 (verify against source). MLX build for the Apple Silicon community.
For authorized security work only.