README.md

# Model Card for V2 Models

## Model Description
This repository contains multiple models trained using the GPT-2 architecture for generating creative stories, superhero names, and abilities. The models are designed to assist in generating narrative content based on user prompts.

## Model Variants
- **Story Model**: Generates stories based on prompts.
- **Name Model**: Generates superhero names based on story context.
- **Abilities Model**: Generates superhero abilities based on story context.
- **Midjourney Model**: Generates mid-journey prompts for storytelling.

## Training Data
The models were trained on a custom dataset stored in `batch_ds_v2.txt`, which includes various story prompts, superhero names, and abilities. The dataset was preprocessed to extract relevant parts for training.

## Training Procedure
- **Framework**: PyTorch with Hugging Face Transformers
- **Model**: GPT-2
- **Training Arguments**:
  - Learning Rate: 1e-4
  - Number of Epochs: 15
  - Max Steps: 5000
  - Batch Size: Auto-detected
  - Gradient Clipping: 1.0
  - Logging Steps: 1

## Evaluation
The models were evaluated based on their ability to generate coherent and contextually relevant text. Specific metrics were not provided, but qualitative assessments were made during development.

## Inference
To use the models for inference, you can send a POST request to the `/generate/<model_path>` endpoint of the Flask application. The input should be a JSON object containing the `input_text` key.

### Example Request
```
json
{
"input_text": "[Ivan Ivanov, Lead Software Engineer, Superhero for Justice, Writing code, fixing issues, solving problems, Masculine, Long Hair, Adult]<endoftext>"
}
```

### Example Response
The response will contain the generated text based on the input prompt.

## Limitations
- The models may generate biased or nonsensical outputs based on the training data.
- They may not always understand complex prompts or context, leading to irrelevant or inaccurate responses.
- The models are sensitive to input phrasing; slight changes in the prompt can yield different results.

## License
This model is released under the MIT License. Please refer to the LICENSE file for more details.

## Citation
If you use this model in your research or applications, please cite it as follows: