Instructions to use ayazfau/GPT2-124M-poetry-RL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ayazfau/GPT2-124M-poetry-RL with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="ayazfau/GPT2-124M-poetry-RL")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ayazfau/GPT2-124M-poetry-RL")
model = AutoModelForCausalLM.from_pretrained("ayazfau/GPT2-124M-poetry-RL")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ayazfau/GPT2-124M-poetry-RL with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ayazfau/GPT2-124M-poetry-RL"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ayazfau/GPT2-124M-poetry-RL",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ayazfau/GPT2-124M-poetry-RL

SGLang

How to use ayazfau/GPT2-124M-poetry-RL with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "ayazfau/GPT2-124M-poetry-RL" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ayazfau/GPT2-124M-poetry-RL",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "ayazfau/GPT2-124M-poetry-RL" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ayazfau/GPT2-124M-poetry-RL",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ayazfau/GPT2-124M-poetry-RL with Docker Model Runner:
```
docker model run hf.co/ayazfau/GPT2-124M-poetry-RL
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

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)
Dataset: 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:

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.

If you use this model, please consider citing it or leaving a star on Hugging Face! ⭐

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Tensor type

F32

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GPT2-124M-poetry-RL