---
license: mit
datasets:
- rajpurkar/squad
base_model:
- google-t5/t5-base
pipeline_tag: question-answering
---
# T5 Question Generator

This repository contains a fine-tuned T5 model for question generation. The model takes an answer and a context paragraph as input and generates a relevant question.

## Model Description

This model is a fine-tuned version of the T5 (Text-to-Text Transfer Transformer) model. It has been trained on a dataset of 60000 non-technical questions from SQuAD and 10000 technical questions. The model is conditioned on the answer and the context to generate a question for which the given answer is the correct response.

## How to Use

You can use this model with the `transformers` library in Python. First, make sure you have the library installed:

```bash
pip install transformers
pip install sentencepiece
```

Then, you can use the following code to load the model and generate a question:

```python
from transformers import T5ForConditionalGeneration, T5Tokenizer

model_name = "Ayush472/T5QuestionGenerator"
model = T5ForConditionalGeneration.from_pretrained(model_name)
tokenizer = T5Tokenizer.from_pretrained(model_name)

context = "The Eiffel Tower is a wrought-iron lattice tower on the Champ de Mars in Paris, France. It is named after the engineer Gustave Eiffel, whose company designed and built the tower."
answer = "Gustave Eiffel"

input_text = f"answer: {answer} context: {context}"
input_ids = tokenizer.encode(input_text, return_tensors="pt")

output = model.generate(input_ids, max_length=100)
generated_question = tokenizer.decode(output[0], skip_special_tokens=True)

print(generated_question)
# Expected output: Who designed the Eiffel Tower?
```

## Model Architecture

The model is based on the T5 architecture. T5 is an encoder-decoder model that is pre-trained on a large corpus of text. It is trained using a text-to-text approach, which means that all NLP tasks are cast as a text-to-text problem.

## About

This model was fine-tuned by Ayush. For any questions or issues, please open an issue in this repository.