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---
language:
- en
license: apache-2.0
library_name: transformers
tags:
- role-play
- fine-tuned
- qwen2.5
base_model:
- Qwen/Qwen2.5-14B-Instruct
pipeline_tag: text-generation
model-index:
- name: oxy-1-small
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: HuggingFaceH4/ifeval
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 62.45
name: strict accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=oxyapi/oxy-1-small
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: BBH
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 41.18
name: normalized accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=oxyapi/oxy-1-small
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: hendrycks/competition_math
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 18.28
name: exact match
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=oxyapi/oxy-1-small
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 16.22
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=oxyapi/oxy-1-small
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MuSR (0-shot)
type: TAUR-Lab/MuSR
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 16.28
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=oxyapi/oxy-1-small
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU-PRO (5-shot)
type: TIGER-Lab/MMLU-Pro
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 44.45
name: accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=oxyapi/oxy-1-small
name: Open LLM Leaderboard
---
![Oxy 1 Small](https://cdn-uploads.huggingface.co/production/uploads/64fb80c8bb362cbf2ff96c7e/tTIVIblPUbTYnlvHQQjXB.png)
## Introduction
**Oxy 1 Small** is a fine-tuned version of the [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/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](https://huggingface.co/oxyapi/oxy-1-small)
- **Base Model**: [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct)
- **Model Type**: Chat Completions
- **Prompt Format**: ChatML
- **License**: Apache-2.0
- **Language**: English
- **Tokenizer**: [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/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:
```python
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](https://www.apache.org/licenses/LICENSE-2.0).
## 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](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_oxyapi__oxy-1-small)
| Metric |Value|
|-------------------|----:|
|Avg. |33.14|
|IFEval (0-Shot) |62.45|
|BBH (3-Shot) |41.18|
|MATH Lvl 5 (4-Shot)|18.28|
|GPQA (0-shot) |16.22|
|MuSR (0-shot) |16.28|
|MMLU-PRO (5-shot) |44.45|
|