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---
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license: apache-2.0
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language:
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- zho
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- eng
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- fra
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- spa
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- por
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- deu
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- ita
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- rus
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- jpn
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- kor
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- vie
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- tha
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- ara
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pipeline_tag: text-generation
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tags:
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- role-play
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- fine-tuned
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- qwen2.5
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base_model:
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- Qwen/Qwen2.5-14B-Instruct
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library_name: transformers
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---
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## Introduction
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**Oxy 1 Small** is a fine-tuned version of the [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/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.
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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.
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## Model Details
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- **Model Name**: Oxy 1 Small
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- **Model ID**: [oxyapi/oxy-1-small](https://huggingface.co/oxyapi/oxy-1-small)
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- **Base Model**: [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2-1.5B)
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- **Model Type**: Chat Completions
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- **Prompt Format**: ChatML
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- **License**: Apache-2.0
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- **Language**: English
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- **Tokenizer**: [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct)
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- **Max Input Tokens**: 32,768
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- **Max Output Tokens**: 8,192
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### Features
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- **Fine-tuned for Role-Play**: Specially trained to generate dynamic and contextually rich role-play dialogues.
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- **Efficient**: Compact model size allows for faster inference and reduced computational resources.
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- **Parameter Support**:
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- `temperature`
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- `top_p`
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- `top_k`
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- `frequency_penalty`
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- `presence_penalty`
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- `max_tokens`
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### Metadata
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- **Owned by**: Oxygen (oxyapi)
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- **Contributors**: TornadoSoftwares
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- **Description**: A Qwen/Qwen2.5-14B-Instruct fine-tune for role-play trained on custom datasets
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## Usage
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To utilize Oxy 1 Small for text generation in role-play scenarios, you can load the model using the Hugging Face Transformers library:
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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tokenizer = AutoTokenizer.from_pretrained("oxyapi/oxy-1-small")
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model = AutoModelForCausalLM.from_pretrained("oxyapi/oxy-1-small")
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prompt = "You are a wise old wizard in a mystical land. A traveler approaches you seeking advice."
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inputs = tokenizer(prompt, return_tensors="pt")
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outputs = model.generate(**inputs, max_length=500)
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response = tokenizer.decode(outputs[0], skip_special_tokens=True)
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print(response)
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```
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## Performance
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Performance benchmarks for Oxy 1 Small are not available at this time. Future updates may include detailed evaluations on relevant datasets.
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## License
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This model is licensed under the [Apache 2.0 License](https://www.apache.org/licenses/LICENSE-2.0).
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## Citation
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If you find Oxy 1 Small useful in your research or applications, please cite it as:
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```
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@misc{oxy1small2024,
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title={Oxy 1 Small: A Fine-Tuned Qwen2.5-14B-Instruct Model for Role-Play},
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author={Oxygen (oxyapi)},
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year={2024},
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howpublished={\url{https://huggingface.co/oxyapi/oxy-1-small}},
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}
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``` |
