--- 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|