---
license: apache-2.0
library_name: transformers
language:
- en
Tags:
- MCQ-Generator
- T5
- text-generation-inference
---
Model Card for Hard_QG_Generator

Model Details

Model Name: Hard_QG_Generator

Model Description: This model can generate MCQs from a given passage.

Model Type: Transformer.

License: Acache-2.0

Author: Lokesh Goenka

Intended Use
Primary Use Cases:
Generating MCQs from a given Passage.
Generate MCQ-based tests for kids

Primary Users:
Teachers, Students, Researchers.

Limitations and Risks
Limitations:
Limitation in the number of generated questions.

Training Data
Data Sources:

NCERT Books
https://epathshala.nic.in//process.php?id=students&type=eTextbooks&ln=en#content

Usage
Example Usage:

Python
hard_model = T5ForConditionalGeneration.from_pretrained("goenkalokesh/Hard_QG_Generator")

hard_tokenizer = T5Tokenizer.from_pretrained("goenkalokesh/Hard_QG_Generator")

--------------
prompt ='''Your Prompt'''

input_text = f"{prompt}: {passage.strip()}"

input_ids = hard_tokenizer.encode(input_text, return_tensors='pt')

outputs = hard_model.generate(

    input_ids, 
    
    max_length=max_length, 
    
    num_beams=num_beams, 
    
    early_stopping=early_stopping,
    
    no_repeat_ngram_size=3
    
)

output_text = hard_tokenizer.decode(outputs[0], skip_special_tokens=True)

print(output_text)