mattcapalbo1432/qwen38-obliterated-cyber

mattcapalbo1432/ qwen38-obliterated-cyber:latest

20 Downloads Updated 14 hours ago

Fine-tuned Qwen 3.8 27B (OBLITERATUS/Qwen3.8-27B-OBLITERATED) specialized for offensive and defensive cybersecurity, penetration testing, reverse engineering, and code execution. Trained on 2,000 high-context technical samples with native 256K context, to

vision tools thinking

ollama run mattcapalbo1432/qwen38-obliterated-cyber

curl http://localhost:11434/api/chat \
  -d '{
    "model": "mattcapalbo1432/qwen38-obliterated-cyber",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

from ollama import chat

response = chat(
    model='mattcapalbo1432/qwen38-obliterated-cyber',
    messages=[{'role': 'user', 'content': 'Hello!'}],
)
print(response.message.content)

import ollama from 'ollama'

const response = await ollama.chat({
  model: 'mattcapalbo1432/qwen38-obliterated-cyber',
  messages: [{role: 'user', content: 'Hello!'}],
})
console.log(response.message.content)

Details

Updated 14 hours ago

14 hours ago

2ee96833441e · 18GB

model

archqwen35

parameters27.3B

quantizationQ4_K_M

17GB

projector

archclip

parameters461M

quantizationBF16

931MB

params

{ "num_ctx": 262144, "repeat_penalty": 1.15, "stop": [ "<|im_start|>", "

114B

template

13B

Readme

Overview

mattcapalbo1432/qwen38-obliterated-cyber is a LoRA fine-tune of OBLITERATUS/Qwen3.8-27B-OBLITERATED (Q4_K_M) trained on 2,000 long-context cybersecurity, exploit analysis, and reverse engineering samples.

Capabilities & Configuration

Context Window: 262,144 tokens (256K)
Supported Features: Native Tool Calling (RENDERER qwen3.5), Reasoning (PARSER qwen3.5), and Vision (mmproj)
Recommended Parameters: temperature 0, repeat_penalty 1.15