--- language: - en license: apache-2.0 library_name: transformers tags: - merge - mergekit - lazymergekit - creative - roleplay - instruct - qwen - model_stock - bfloat16 base_model: - newsbang/Homer-v0.5-Qwen2.5-7B - allknowingroger/HomerSlerp1-7B - bunnycore/Qwen2.5-7B-Instruct-Fusion - bunnycore/Qandora-2.5-7B-Creative model-index: - name: Qwen2.5-7B-HomerCreative-Mix 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: 78.35 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ZeroXClem/Qwen2.5-7B-HomerCreative-Mix 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: 36.77 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ZeroXClem/Qwen2.5-7B-HomerCreative-Mix 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: 32.33 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ZeroXClem/Qwen2.5-7B-HomerCreative-Mix 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: 6.6 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ZeroXClem/Qwen2.5-7B-HomerCreative-Mix 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: 13.77 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ZeroXClem/Qwen2.5-7B-HomerCreative-Mix 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: 38.3 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ZeroXClem/Qwen2.5-7B-HomerCreative-Mix name: Open LLM Leaderboard --- # ZeroXClem/Qwen2.5-7B-HomerCreative-Mix **ZeroXClem/Qwen2.5-7B-HomerCreative-Mix** is an advanced language model meticulously crafted by merging four pre-trained models using the powerful [mergekit](https://github.com/cg123/mergekit) framework. This fusion leverages the **Model Stock** merge method to combine the creative prowess of **Qandora**, the instructive capabilities of **Qwen-Instruct-Fusion**, the sophisticated blending of **HomerSlerp1**, and the foundational conversational strengths of **Homer-v0.5-Qwen2.5-7B**. The resulting model excels in creative text generation, contextual understanding, and dynamic conversational interactions. ## 🚀 Merged Models This model merge incorporates the following: - [**bunnycore/Qandora-2.5-7B-Creative**](https://huggingface.co/bunnycore/Qandora-2.5-7B-Creative): Specializes in creative text generation, enhancing the model's ability to produce imaginative and diverse content. - [**bunnycore/Qwen2.5-7B-Instruct-Fusion**](https://huggingface.co/bunnycore/Qwen2.5-7B-Instruct-Fusion): Focuses on instruction-following capabilities, improving the model's performance in understanding and executing user commands. - [**allknowingroger/HomerSlerp1-7B**](https://huggingface.co/allknowingroger/HomerSlerp1-7B): Utilizes spherical linear interpolation (SLERP) to blend model weights smoothly, ensuring a harmonious integration of different model attributes. - [**newsbang/Homer-v0.5-Qwen2.5-7B**](https://huggingface.co/newsbang/Homer-v0.5-Qwen2.5-7B): Acts as the foundational conversational model, providing robust language comprehension and generation capabilities. ## 🧩 Merge Configuration The configuration below outlines how the models are merged using the **Model Stock** method. This approach ensures a balanced and effective integration of the unique strengths from each source model. ```yaml # Merge configuration for ZeroXClem/Qwen2.5-7B-HomerCreative-Mix using Model Stock models: - model: bunnycore/Qandora-2.5-7B-Creative - model: bunnycore/Qwen2.5-7B-Instruct-Fusion - model: allknowingroger/HomerSlerp1-7B merge_method: model_stock base_model: newsbang/Homer-v0.5-Qwen2.5-7B normalize: false int8_mask: true dtype: bfloat16 ``` ### Key Parameters - **Merge Method (`merge_method`):** Utilizes the **Model Stock** method, as described in [Model Stock](https://arxiv.org/abs/2403.19522), to effectively combine multiple models by leveraging their strengths. - **Models (`models`):** Specifies the list of models to be merged: - **bunnycore/Qandora-2.5-7B-Creative:** Enhances creative text generation. - **bunnycore/Qwen2.5-7B-Instruct-Fusion:** Improves instruction-following capabilities. - **allknowingroger/HomerSlerp1-7B:** Facilitates smooth blending of model weights using SLERP. - **Base Model (`base_model`):** Defines the foundational model for the merge, which is **newsbang/Homer-v0.5-Qwen2.5-7B** in this case. - **Normalization (`normalize`):** Set to `false` to retain the original scaling of the model weights during the merge. - **INT8 Mask (`int8_mask`):** Enabled (`true`) to apply INT8 quantization masking, optimizing the model for efficient inference without significant loss in precision. - **Data Type (`dtype`):** Uses `bfloat16` to maintain computational efficiency while ensuring high precision. ## 🏆 Performance Highlights - **Creative Text Generation:** Enhanced ability to produce imaginative and diverse content suitable for creative writing, storytelling, and content creation. - **Instruction Following:** Improved performance in understanding and executing user instructions, making the model more responsive and accurate in task execution. - **Optimized Inference:** INT8 masking and `bfloat16` data type contribute to efficient computation, enabling faster response times without compromising quality. ## 🎯 Use Case & Applications **ZeroXClem/Qwen2.5-7B-HomerCreative-Mix** is designed to excel in environments that demand both creative generation and precise instruction following. Ideal applications include: - **Creative Writing Assistance:** Aiding authors and content creators in generating imaginative narratives, dialogues, and descriptive text. - **Interactive Storytelling and Role-Playing:** Enhancing dynamic and engaging interactions in role-playing games and interactive storytelling platforms. - **Educational Tools and Tutoring Systems:** Providing detailed explanations, answering questions, and assisting in educational content creation with contextual understanding. - **Technical Support and Customer Service:** Offering accurate and contextually relevant responses in technical support scenarios, improving user satisfaction. - **Content Generation for Marketing:** Creating compelling and diverse marketing copy, social media posts, and promotional material with creative flair. ## 📝 Usage To utilize **ZeroXClem/Qwen2.5-7B-HomerCreative-Mix**, follow the steps below: ### Installation First, install the necessary libraries: ```bash pip install -qU transformers accelerate ``` ### Example Code Below is an example of how to load and use the model for text generation: ```python from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline import torch # Define the model name model_name = "ZeroXClem/Qwen2.5-7B-HomerCreative-Mix" # Load the tokenizer tokenizer = AutoTokenizer.from_pretrained(model_name) # Load the model model = AutoModelForCausalLM.from_pretrained( model_name, torch_dtype=torch.bfloat16, device_map="auto" ) # Initialize the pipeline text_generator = pipeline( "text-generation", model=model, tokenizer=tokenizer, torch_dtype=torch.bfloat16, device_map="auto" ) # Define the input prompt prompt = "Once upon a time in a land far, far away," # Generate the output outputs = text_generator( prompt, max_new_tokens=150, do_sample=True, temperature=0.7, top_k=50, top_p=0.95 ) # Print the generated text print(outputs[0]["generated_text"]) ``` ### Notes - **Fine-Tuning:** This merged model may require fine-tuning to optimize performance for specific applications or domains. - **Resource Requirements:** Ensure that your environment has sufficient computational resources, especially GPU-enabled hardware, to handle the model efficiently during inference. - **Customization:** Users can adjust parameters such as `temperature`, `top_k`, and `top_p` to control the creativity and diversity of the generated text. ## 📜 License This model is open-sourced under the **Apache-2.0 License**. ## 💡 Tags - `merge` - `mergekit` - `model_stock` - `Qwen` - `Homer` - `Creative` - `ZeroXClem/Qwen2.5-7B-HomerCreative-Mix` - `bunnycore/Qandora-2.5-7B-Creative` - `bunnycore/Qwen2.5-7B-Instruct-Fusion` - `allknowingroger/HomerSlerp1-7B` - `newsbang/Homer-v0.5-Qwen2.5-7B` --- # [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_ZeroXClem__Qwen2.5-7B-HomerCreative-Mix) | Metric |Value| |-------------------|----:| |Avg. |34.35| |IFEval (0-Shot) |78.35| |BBH (3-Shot) |36.77| |MATH Lvl 5 (4-Shot)|32.33| |GPQA (0-shot) | 6.60| |MuSR (0-shot) |13.77| |MMLU-PRO (5-shot) |38.30|