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---
license: mit
language:
- en
tags:
- pytorch
- custom-model
- hello-world
- demo
- example
library_name: transformers
pipeline_tag: text-generation
---
# Hello World AI Model
[](https://huggingface.co/vinothkannans/hello-world)
A simple demonstration model built with Hugging Face Transformers that always returns "Hello World". This model serves as a minimal example of creating custom models using the Transformers library.
## Model Description
The Hello World AI Model is a custom PyTorch model that extends `PreTrainedModel` from the Hugging Face Transformers library. It's designed as a learning example and template for building custom models.
- **Developed by:** Vinoth Kannan
- **Model type:** Custom PyTorch Model
- **Language(s):** English
- **License:** MIT
## Model Details
### Model Architecture
The model consists of:
- A single linear layer (`nn.Linear(1, 1)`) for demonstration purposes
- A forward method that returns `{"text": "Hello World"}` regardless of input
### Training
This is a demonstration model and does not require training. It's a static model that always returns the same output.
## Usage
### Using Transformers
```python
from transformers import AutoModel, AutoConfig
# Load the model
model = AutoModel.from_pretrained("vinothkannans/hello-world")
config = AutoConfig.from_pretrained("vinothkannans/hello-world")
# Use the model
output = model.forward()
print(output) # {'text': 'Hello World'}
```
### Using PyTorch
```python
import torch
from transformers import AutoModel
model = AutoModel.from_pretrained("vinothkannans/hello-world")
model.eval()
with torch.no_grad():
output = model.forward()
print(output) # {'text': 'Hello World'}
```
## Model Card Contact
For questions or issues, please contact [vinothkannans](https://huggingface.co/vinothkannans) on Hugging Face.
## Limitations
This is a demonstration model for the learing production purposes. It always returns the same output regardless of input.
## Citation
```bibtex
@misc{hello-world-model,
author = {Vinoth Kannan},
title = {Hello World AI Model},
year = {2025},
publisher = {Hugging Face},
howpublished = {\url{https://huggingface.co/vinothkannans/hello-world}}
}
```
## License
This model is licensed under the MIT License. See the [LICENSE](LICENSE) file for more details.
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