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QuantFactory/oxy-1-small-GGUF
oxy-1-small-GGUF is a text generation model from QuantFactory. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
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From the Hugging Face model README
This is quantized version of oxyapi/oxy-1-small created using llama.cpp

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.
temperaturetop_ptop_kfrequency_penaltypresence_penaltymax_tokensTo 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 benchmarks for Oxy 1 Small are not available at this time. Future updates may include detailed evaluations on relevant datasets.
This model is licensed under the Apache 2.0 License.
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}},
}