README.md

---
tags:
- text-generation
- gpt2
license: gpl-3.0
datasets:
- bookcorpus
metrics:
- perplexity
model-index:
- name: basic-text-generator
  results:
  - task:
      type: text-generation
    dataset:
      name: bookcorpus
      type: bookcorpus
    metrics:
    - name: Perplexity
      type: perplexity
      value: 25.3
---

# Basic Text Generator

## Overview

This is a fine-tuned GPT-2 model for general text generation. It can continue prompts, generate stories, or create coherent paragraphs based on input text. Trained on a diverse corpus for broad applicability.

## Model Architecture

- Base Model: GPT-2
- Layers: 12
- Hidden Size: 768
- Attention Heads: 12
- Context Window: 1024 tokens

## Intended Use

Suitable for creative writing, content generation, or prototyping language-based applications.

## Limitations

- May generate biased or inappropriate content based on training data.
- Outputs can be repetitive or nonsensical for long generations.
- Not optimized for specific domains like code or math.

## Example Code

```python
from transformers import pipeline

generator = pipeline("text-generation", model="user/basic-text-generator")
result = generator("Once upon a time,", max_length=50)
print(result[0]['generated_text'])
# "Once upon a time, in a land far away..."