---
language: en
tags:
- operating-systems
- reasoning
- education
- computer-science
datasets:
- custom
metrics:
- accuracy
widget:
- text: "Question: What is a process in operating systems? Reasoning:"
  example_title: "Process Explanation"
- text: "Question: How does virtual memory work? Reasoning:"
  example_title: "Virtual Memory"
---

# Operating System Reasoning Model

## Model Description

This model is specifically fine-tuned for reasoning about Operating Systems concepts. It can:

- Explain OS concepts with step-by-step reasoning
- Solve OS-related problems
- Compare different OS mechanisms
- Provide educational explanations for students

## Training Data

The model was trained on content from multiple authoritative Operating Systems textbooks and resources:

- **OSTEP (Operating Systems: Three Easy Pieces)** - 0 chapters
- **xv6 Documentation** - System implementation details
- **Academic OS Resources** - Additional educational content

Total training examples: 3354

## Usage

```python
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("jahidhasan/os-reasoning-model")
model = AutoModelForCausalLM.from_pretrained("jahidhasan/os-reasoning-model")

# Generate reasoning
question = "What is a deadlock in operating systems?"
prompt = f"Question: {question}\nReasoning:"

inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_length=200, temperature=0.7)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response)
```

## Model Architecture

- **Base Model**: distilbert/distilgpt2
- **Parameters**: 81,917,184
- **Fine-tuning**: Specialized for OS domain reasoning

## Performance

The model demonstrates strong performance on:
- Concept explanation tasks
- Problem-solving scenarios  
- Comparative analysis
- Educational Q&A

## Limitations

- Focused specifically on Operating Systems domain
- May not perform well on general reasoning tasks
- Requires clear, structured questions for best results

## Citation

```bibtex
@misc{os-reasoning-model,
  author = {Jahid Hasan},
  title = {Operating System Reasoning Model},
  year = {2025},
  publisher = {Hugging Face},
  howpublished = {\url{https://huggingface.co/jahidhasan/os-reasoning-model}}
}
```

## Training Details

- **Training Epochs**: 5
- **Learning Rate**: 3e-5
- **Batch Size**: 16
- **Training Time**: Unknown

## Educational Use

This model is particularly useful for:
- Computer Science students learning OS concepts
- Educators creating OS curriculum
- Self-study and review sessions
- Assignment and project assistance

---

*Trained with ❤️ for OS education*