metadata
base_model: unsloth/mistral-nemo-base-2407-bnb-4bit
tags:
- text-generation-inference
- transformers
- unsloth
- mistral
- trl
- question-generation
license: apache-2.0
language:
- en
pipeline_tag: text-generation
inference: true
framework: pytorch
widgets:
- inputs:
instruction: >-
Generate a multiple-choice question (MCQ) based on the passage, provide
options, and indicate the correct option.
context: >-
Photosynthesis is the process by which plants convert sunlight into
energy.
outputs:
question: >-
What is the primary process by which plants convert sunlight into
energy?
options:
- A. Photosynthesis
- B. Respiration
- C. Fermentation
- D. Transpiration
correct_option: A
example_title: MCQ Question Generation
- inputs:
instruction: >-
Generate a multiple-choice question (MCQ) based on the passage, provide
options, and indicate the correct option.
context: >-
Cellular respiration is a metabolic process that converts nutrients into
ATP, the energy currency of the cell.
outputs:
question: What is the main purpose of cellular respiration?
options:
- A. Converting nutrients into ATP
- B. Producing oxygen
- C. Generating heat
- D. Breaking down proteins
correct_option: A
example_title: Cellular Respiration MCQ
- inputs:
instruction: Generate a multiple-choice question (MCQ) based on a historical passage
context: >-
The Industrial Revolution began in Great Britain in the late 18th
century, transforming manufacturing processes through mechanization.
outputs:
question: Where did the Industrial Revolution primarily originate?
options:
- A. United States
- B. France
- C. Great Britain
- D. Germany
correct_option: C
example_title: Industrial Revolution MCQ
- inputs:
instruction: Generate a multiple-choice question about environmental science
context: >-
Biodiversity refers to the variety of life forms within a given
ecosystem, including genetic, species, and ecological diversity.
outputs:
question: What does biodiversity encompass?
options:
- A. Only plant species
- B. Genetic, species, and ecological diversity
- C. Only animal populations
- D. Human interactions with nature
correct_option: B
example_title: Biodiversity MCQ
library_name: transformers
Uploaded model
- Developed by: kanoza
- License: apache-2.0
- Finetuned from model : unsloth/mistral-nemo-base-2407-bnb-4bit
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
Mistral Nemo MCQ Question Generator
Overview
A fine-tuned Mistral Nemo model specializing in generating multiple-choice questions (MCQs) across various domains.
Model Details
- Base Model: Mistral Nemo Base 2407
- Fine-Tuning: LoRA with 4-bit quantization
- Training Dataset: SciQ
- Primary Task: Automated MCQ Generation
Key Features
- Scientific domain question generation
- Supports multiple context types
- High-quality, contextually relevant options
- Configurable question complexity
Installation
pip install transformers unsloth
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("path/to/model")
tokenizer = AutoTokenizer.from_pretrained("path/to/model")
Usage Example
def generate_mcq(context, instruction):
prompt = f"""
Instruction: {instruction}
Context: {context}
"""
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=128)
return tokenizer.decode(outputs[0])
# Example application
context = "Photosynthesis converts sunlight into plant energy."
mcq = generate_mcq(context, "Create a multiple-choice question")
print(mcq)
Performance Metrics
- BERTScore F1: [Placeholder]
- ROUGE-1 F1: [Placeholder]
- Generation Accuracy: [Placeholder]
Limitations
- Primarily trained on scientific content
- Requires careful prompt engineering
- Potential bias in question generation
Ethical Considerations
- Intended for educational research
- Users should verify generated content
License
Apache 2.0
Contributing
Contributions welcome! Please open issues/PRs on GitHub.
