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)