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--- |
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language: en |
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tags: |
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- operating-systems |
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- reasoning |
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- education |
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- computer-science |
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datasets: |
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- custom |
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metrics: |
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- accuracy |
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widget: |
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- text: "Question: What is a process in operating systems? Reasoning:" |
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example_title: "Process Explanation" |
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- text: "Question: How does virtual memory work? Reasoning:" |
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example_title: "Virtual Memory" |
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--- |
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# Operating System Reasoning Model |
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## Model Description |
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This model is specifically fine-tuned for reasoning about Operating Systems concepts. It can: |
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- Explain OS concepts with step-by-step reasoning |
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- Solve OS-related problems |
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- Compare different OS mechanisms |
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- Provide educational explanations for students |
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## Training Data |
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The model was trained on content from multiple authoritative Operating Systems textbooks and resources: |
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- **OSTEP (Operating Systems: Three Easy Pieces)** - 0 chapters |
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- **xv6 Documentation** - System implementation details |
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- **Academic OS Resources** - Additional educational content |
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Total training examples: 3354 |
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## Usage |
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```python |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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tokenizer = AutoTokenizer.from_pretrained("jahidhasan/os-reasoning-model") |
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model = AutoModelForCausalLM.from_pretrained("jahidhasan/os-reasoning-model") |
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# Generate reasoning |
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question = "What is a deadlock in operating systems?" |
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prompt = f"Question: {question}\nReasoning:" |
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inputs = tokenizer(prompt, return_tensors="pt") |
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outputs = model.generate(**inputs, max_length=200, temperature=0.7) |
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response = tokenizer.decode(outputs[0], skip_special_tokens=True) |
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print(response) |
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``` |
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## Model Architecture |
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- **Base Model**: distilbert/distilgpt2 |
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- **Parameters**: 81,917,184 |
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- **Fine-tuning**: Specialized for OS domain reasoning |
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## Performance |
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The model demonstrates strong performance on: |
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- Concept explanation tasks |
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- Problem-solving scenarios |
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- Comparative analysis |
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- Educational Q&A |
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## Limitations |
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- Focused specifically on Operating Systems domain |
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- May not perform well on general reasoning tasks |
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- Requires clear, structured questions for best results |
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## Citation |
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```bibtex |
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@misc{os-reasoning-model, |
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author = {Jahid Hasan}, |
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title = {Operating System Reasoning Model}, |
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year = {2025}, |
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publisher = {Hugging Face}, |
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howpublished = {\url{https://huggingface.co/jahidhasan/os-reasoning-model}} |
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} |
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``` |
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## Training Details |
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- **Training Epochs**: 5 |
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- **Learning Rate**: 3e-5 |
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- **Batch Size**: 16 |
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- **Training Time**: Unknown |
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## Educational Use |
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This model is particularly useful for: |
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- Computer Science students learning OS concepts |
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- Educators creating OS curriculum |
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- Self-study and review sessions |
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- Assignment and project assistance |
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--- |
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*Trained with ❤️ for OS education* |
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