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  This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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  [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
 
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  This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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+ # Mistral Nemo MCQ Question Generator
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+
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+ ## Overview
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+ A fine-tuned Mistral Nemo model specializing in generating multiple-choice questions (MCQs) across various domains.
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+
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+ ## Model Details
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+ - **Base Model**: Mistral Nemo Base 2407
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+ - **Fine-Tuning**: LoRA with 4-bit quantization
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+ - **Training Dataset**: SciQ
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+ - **Primary Task**: Automated MCQ Generation
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+
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+ ## Key Features
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+ - Scientific domain question generation
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+ - Supports multiple context types
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+ - High-quality, contextually relevant options
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+ - Configurable question complexity
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+
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+ ## Installation
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+ ```python
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+ pip install transformers unsloth
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+ model = AutoModelForCausalLM.from_pretrained("path/to/model")
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+ tokenizer = AutoTokenizer.from_pretrained("path/to/model")
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+ ```
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+
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+ ## Usage Example
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+ ```python
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+ def generate_mcq(context, instruction):
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+ prompt = f"""
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+ Instruction: {instruction}
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+ Context: {context}
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+ """
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+ inputs = tokenizer(prompt, return_tensors="pt")
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+ outputs = model.generate(**inputs, max_new_tokens=128)
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+ return tokenizer.decode(outputs[0])
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+
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+ # Example application
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+ context = "Photosynthesis converts sunlight into plant energy."
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+ mcq = generate_mcq(context, "Create a multiple-choice question")
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+ print(mcq)
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+ ```
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+
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+ ## Performance Metrics
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+ - BERTScore F1: [Placeholder]
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+ - ROUGE-1 F1: [Placeholder]
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+ - Generation Accuracy: [Placeholder]
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+
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+ ## Limitations
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+ - Primarily trained on scientific content
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+ - Requires careful prompt engineering
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+ - Potential bias in question generation
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+
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+ ## Ethical Considerations
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+ - Intended for educational research
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+ - Users should verify generated content
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+
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+ ## License
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+ Apache 2.0
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+
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+ ## Contributing
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+ Contributions welcome! Please open issues/PRs on GitHub.
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+
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  [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)