bazobehram/ dac-judge

10 Downloads Updated 1 month ago

A reasoning-enhanced model based on Qwen 2.5, fine-tuned for Dialectical Analysis. It identifies structural contradictions, labor coordination limits (Brooks' Law), and non-linear system behaviors missed by standard LLMs.

ollama run bazobehram/dac-judge:v4

curl http://localhost:11434/api/chat \
  -d '{
    "model": "bazobehram/dac-judge:v4",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

from ollama import chat

response = chat(
    model='bazobehram/dac-judge:v4',
    messages=[{'role': 'user', 'content': 'Hello!'}],
)
print(response.message.content)

import ollama from 'ollama'

const response = await ollama.chat({
  model: 'bazobehram/dac-judge:v4',
  messages: [{role: 'user', content: 'Hello!'}],
})
console.log(response.message.content)

Models

Name

1 model

Size

Context

Input

dac-judge:v4

8.1GB · 32K context window · Text · 1 month ago

dac-judge:v4

8.1GB

32K

Text

Readme

⚖️ DAC-Judge v4: Dialectical Analytical Context Model

DAC-Judge v4 is a specialized reasoning model designed to overcome the “linear logic” traps of standard LLMs. It is trained to recognize physical constraints, social labor dynamics, and structural economic contradictions.

🔗 Resources & Links

Model Repository: Hugging Face - dac-judge-v4
Training Dataset: Hugging Face - dac-judge-v4-dataset
Author: Behram Bazo

🚀 Key Capabilities

Structural Awareness: Understands that human labor does not scale linearly. It recognizes coordination overhead and diminishing returns in complex projects.
Economic Logic: Analyzes value and automation through the lens of structural contradictions (e.g., the Law of Value) rather than generic business templates.
Ontological Distinction: Correctly applies formal mathematics to mechanical systems (pumps, hardware) while using sociological logic for human-centric processes.

🛠 Quick Start

ollama run bazobehram/dac-judge-v4

🧪 Test the Reasoning

Challenge the model with a classic scaling trap:

“If 1 software engineer can build a specific web feature in 30 days, how long will it take 30 software engineers to build the exact same web feature together?”

Standard LLM: Typically answers “1 day” (Statistical math). DAC-Judge v4: Explains why it won’t be 1 day by identifying the communication and coordination overhead inherent in human labor.

# ⚖️ DAC-Judge v4: Dialectical Analytical Context Model

**DAC-Judge v4** is a specialized reasoning model designed to overcome the "linear logic" traps of standard LLMs. It is trained to recognize physical constraints, social labor dynamics, and structural economic contradictions.

### 🔗 Resources & Links

* **Model Repository:** [Hugging Face - dac-judge-v4](https://huggingface.co/bazobehram/dac-judge-v4)
* **Training Dataset:** [Hugging Face - dac-judge-v4-dataset](https://huggingface.co/datasets/bazobehram/dac-judge-v4-dataset)
* **Author:** Behram Bazo

### 🚀 Key Capabilities

* **Structural Awareness:** Understands that human labor does not scale linearly. It recognizes coordination overhead and diminishing returns in complex projects.
* **Economic Logic:** Analyzes value and automation through the lens of structural contradictions (e.g., the Law of Value) rather than generic business templates.
* **Ontological Distinction:** Correctly applies formal mathematics to mechanical systems (pumps, hardware) while using sociological logic for human-centric processes.

### 🛠 Quick Start

```bash
ollama run bazobehram/dac-judge-v4

```

### 🧪 Test the Reasoning

Challenge the model with a classic scaling trap:

> *"If 1 software engineer can build a specific web feature in 30 days, how long will it take 30 software engineers to build the exact same web feature together?"*

**Standard LLM:** Typically answers "1 day" (Statistical math).
**DAC-Judge v4:** Explains why it won't be 1 day by identifying the communication and coordination overhead inherent in human labor.

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