---
tags:
- text-generation
- acceptance-criteria
- user-story
- gpt2
---

# User Story GPT-2 Model

This is a fine-tuned GPT-2 model trained on user stories and acceptance criteria.It generates acceptance criteria for a given user story in natural language.


# User Story GPT-2 Model

This is a fine-tuned **GPT-2** model trained on **user stories** and **acceptance criteria**. It generates acceptance criteria for a given user story in natural language. This model can be used in **claims processing applications** or for any other task that requires generating user stories and corresponding acceptance criteria.

## Model Overview
The model is based on the GPT-2 architecture and has been fine-tuned specifically to generate user stories and acceptance criteria in the following format:

1. **User Story**: Describes a feature or requirement from the user's perspective.
2. **Acceptance Criteria**: Specifies the conditions that need to be met for the user story to be considered complete.

## How to Use the Model

### Example Code:

You can use the model in your Python applications using the Hugging Face **Transformers** library. Here’s an example to get started:

```python
from transformers import pipeline

# Load the fine-tuned model
generator = pipeline('text-generation', model='USACCAI/USACCAIV1')

# Define a user story prompt
prompt = "As a claims processor, when I check if a treatment occurred after the person has died, I need to show a message."

# Generate acceptance criteria
result = generator(prompt, max_length=100)

# Print the generated output
print(result)