Introduction

Oxy 1 Small is a fine-tuned version of the Qwen/Qwen2.5-14B-Instruct language model, specialized for role-play scenarios. Despite its small size, it delivers impressive performance in generating engaging dialogues and interactive storytelling.

Developed by Oxygen (oxyapi), with contributions from TornadoSoftwares, Oxy 1 Small aims to provide an accessible and efficient language model for creative and immersive role-play experiences.

Model Details

• Model Name: Oxy 1 Small
• Model ID: oxyapi/oxy-1-small
• Base Model: Qwen/Qwen2.5-14B-Instruct
• Model Type: Chat Completions
• Prompt Format: ChatML
• License: Apache-2.0
• Language: English
• Tokenizer: Qwen/Qwen2.5-14B-Instruct
• Max Input Tokens: 32,768
• Max Output Tokens: 8,192

Features

• Fine-tuned for Role-Play: Specially trained to generate dynamic and contextually rich role-play dialogues.
• Efficient: Compact model size allows for faster inference and reduced computational resources.
• Parameter Support:
  • temperature
  • top_p
  • top_k
  • frequency_penalty
  • presence_penalty
  • max_tokens

Metadata

• Owned by: Oxygen (oxyapi)
• Contributors: TornadoSoftwares
• Description: A Qwen/Qwen2.5-14B-Instruct fine-tune for role-play trained on custom datasets

Usage

To utilize Oxy 1 Small for text generation in role-play scenarios, you can load the model using the Hugging Face Transformers library:

from transformers import AutoModelForCausalLM, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("oxyapi/oxy-1-small")
model = AutoModelForCausalLM.from_pretrained("oxyapi/oxy-1-small")

prompt = "You are a wise old wizard in a mystical land. A traveler approaches you seeking advice."
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_length=500)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response)

Performance

Performance benchmarks for Oxy 1 Small are not available at this time. Future updates may include detailed evaluations on relevant datasets.

License

This model is licensed under the Apache 2.0 License.

Citation

If you find Oxy 1 Small useful in your research or applications, please cite it as:

@misc{oxy1small2024,
  title={Oxy 1 Small: A Fine-Tuned Qwen2.5-14B-Instruct Model for Role-Play},
  author={Oxygen (oxyapi)},
  year={2024},
  howpublished={\url{https://huggingface.co/oxyapi/oxy-1-small}},
}

Open LLM Leaderboard Evaluation Results

Detailed results can be found here