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--- |
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language: |
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- en |
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license: apache-2.0 |
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library_name: transformers |
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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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pipeline_tag: text-generation |
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model-index: |
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- name: oxy-1-small |
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results: |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: IFEval (0-Shot) |
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type: HuggingFaceH4/ifeval |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: inst_level_strict_acc and prompt_level_strict_acc |
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value: 62.45 |
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name: strict accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=oxyapi/oxy-1-small |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: BBH (3-Shot) |
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type: BBH |
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args: |
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num_few_shot: 3 |
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metrics: |
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- type: acc_norm |
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value: 41.18 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=oxyapi/oxy-1-small |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MATH Lvl 5 (4-Shot) |
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type: hendrycks/competition_math |
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args: |
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num_few_shot: 4 |
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metrics: |
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- type: exact_match |
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value: 18.28 |
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name: exact match |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=oxyapi/oxy-1-small |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: GPQA (0-shot) |
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type: Idavidrein/gpqa |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: acc_norm |
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value: 16.22 |
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name: acc_norm |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=oxyapi/oxy-1-small |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MuSR (0-shot) |
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type: TAUR-Lab/MuSR |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: acc_norm |
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value: 16.28 |
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name: acc_norm |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=oxyapi/oxy-1-small |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MMLU-PRO (5-shot) |
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type: TIGER-Lab/MMLU-Pro |
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config: main |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 44.45 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=oxyapi/oxy-1-small |
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name: Open LLM Leaderboard |
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--- |
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![Oxy 1 Small](https://cdn-uploads.huggingface.co/production/uploads/64fb80c8bb362cbf2ff96c7e/tTIVIblPUbTYnlvHQQjXB.png) |
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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/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/Qwen2.5-14B-Instruct) |
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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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``` |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_oxyapi__oxy-1-small) |
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| Metric |Value| |
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|-------------------|----:| |
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|Avg. |33.14| |
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|IFEval (0-Shot) |62.45| |
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|BBH (3-Shot) |41.18| |
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|MATH Lvl 5 (4-Shot)|18.28| |
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|GPQA (0-shot) |16.22| |
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|MuSR (0-shot) |16.28| |
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|MMLU-PRO (5-shot) |44.45| |
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