---
language: en
tags:
  - text-generation
  - poetry
  - gpt2
  - rl
license: mit
datasets:
  - biglam/gutenberg-poetry-corpus
model_name: GPT2-124 Poetry RL
library_name: transformers
---

# GPT2-124 Fine-Tuned on Poetry with Reinforcement Learning (RL)

## Model Description
This model, **GPT2-124 Poetry RL**, is a fine-tuned version of GPT-2 trained on the **Gutenberg Poetry Corpus** with **Reinforcement Learning (RL)**. The model is optimized for poetic generation with enhanced stylistic qualities such as **rhyme, coherence, and creativity**.

## Training Details
- **Base Model**: [GPT-2 (124M)](https://huggingface.co/gpt2)
- **Dataset**: [Gutenberg Poetry Corpus](https://huggingface.co/datasets/biglam/gutenberg-poetry-corpus)
- **Fine-Tuning Approach**:
  - Supervised fine-tuning on poetry lines.
  - RL with custom reward functions:
    - **Rhyme Reward**: Encourages rhyming lines.
    - **Coherence Reward**: Ensures logical flow.
    - **Creativity Reward**: Penalizes repetition and rewards unique wording.

## How to Use
You can generate poetry using the `transformers` library:

```python
from transformers import GPT2LMHeadModel, GPT2Tokenizer

tokenizer = GPT2Tokenizer.from_pretrained("ayazfau/GPT2-124-poetry-RL")
model = GPT2LMHeadModel.from_pretrained("ayazfau/GPT2-124-poetry-RL")

def generate_poetry(prompt, max_length=50):
    input_ids = tokenizer(prompt, return_tensors="pt").input_ids
    output = model.generate(input_ids, max_new_tokens=max_length, do_sample=True, top_k=50, top_p=0.95, pad_token_id=tokenizer.eos_token_id)
    return tokenizer.decode(output[0], skip_special_tokens=True)

print(generate_poetry("fear kill dreams,"))
```

## Model Performance
- The model generates **rhyming** and **coherent** poetic lines.
- Works well for **short-form poetry** and **lyrical content**.
- Still has some limitations in **long-form poetry structure**.

## License
This model is released under the **MIT License**. Feel free to use it for research and creative writing!

## Acknowledgments
- Trained using **PyTorch Lightning** and **Hugging Face Transformers**.
- Special thanks to the **Gutenberg Poetry Corpus** for providing high-quality literary data.

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