---
base_model:
- openai-community/gpt2
language:
- en
- ta
license: mit
tags:
- gpt2
- text-generation
- QnQ
pipeline_tag: question-answering
---

# QnQGPT Model

This is a custom GPT model based on GPT-2 architecture.

## Model Details

- Model Type: GPT-2
- Base Model: gpt2
- Training Data: [Describe your training data]
- Use Cases: [Describe intended use cases]

## Usage

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("karthikqnq/qnqgpt")
tokenizer = AutoTokenizer.from_pretrained("karthikqnq/qnqgpt")

# Generate text
text = "Hello, how are"
inputs = tokenizer(text, return_tensors="pt")
outputs = model.generate(**inputs, max_length=50)
result = tokenizer.decode(outputs[0])
print(result)
```

## Training Details

[Add your training details here]

## Limitations

[Add model limitations here]

## License

This model is released under the MIT License.