--- language: - en license: apache-2.0 library_name: transformers tags: - merge - mergekit - lazymergekit - bfloat16 - roleplay - creative - instruct - anvita - qwen - nerd - homer - Qandora base_model: - bunnycore/Qandora-2.5-7B-Creative - allknowingroger/HomerSlerp1-7B - sethuiyer/Qwen2.5-7B-Anvita - fblgit/cybertron-v4-qw7B-MGS - jeffmeloy/Qwen2.5-7B-nerd-uncensored-v1.0 - newsbang/Homer-v0.5-Qwen2.5-7B pipeline_tag: text-generation model-index: - name: Qwen2.5-7B-HomerAnvita-NerdMix 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: 77.08 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix 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: 36.58 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix 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: 29.53 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix 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: 9.28 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix 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: 14.41 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix 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: 38.13 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix name: Open LLM Leaderboard --- [![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory) # QuantFactory/Qwen2.5-7B-HomerAnvita-NerdMix-GGUF This is quantized version of [ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix](https://huggingface.co/ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix) created using llama.cpp # Original Model Card # ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix **ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix** is an advanced language model meticulously crafted by merging five 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**, the mathematical precision of **Cybertron-MGS**, and the uncensored expertise of **Qwen-Nerd**. The resulting model excels in creative text generation, contextual understanding, technical reasoning, 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. - [**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. - [**sethuiyer/Qwen2.5-7B-Anvita**](https://huggingface.co/sethuiyer/Qwen2.5-7B-Anvita): Focuses on instruction-following capabilities, improving the model's performance in understanding and executing user commands. - [**fblgit/cybertron-v4-qw7B-MGS**](https://huggingface.co/fblgit/cybertron-v4-qw7B-MGS): Enhances mathematical reasoning and precision, enabling the model to handle complex computational tasks effectively. - [**jeffmeloy/Qwen2.5-7B-nerd-uncensored-v1.0**](https://huggingface.co/jeffmeloy/Qwen2.5-7B-nerd-uncensored-v1.0): Provides uncensored expertise and robust technical knowledge, making the model suitable for specialized technical support and information retrieval. - [**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-HomerAnvita-NerdMix using Model Stock models: - model: bunnycore/Qandora-2.5-7B-Creative - model: allknowingroger/HomerSlerp1-7B - model: sethuiyer/Qwen2.5-7B-Anvita - model: fblgit/cybertron-v4-qw7B-MGS - model: jeffmeloy/Qwen2.5-7B-nerd-uncensored-v1.0 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. - **allknowingroger/HomerSlerp1-7B:** Facilitates smooth blending of model weights using SLERP. - **sethuiyer/Qwen2.5-7B-Anvita:** Improves instruction-following capabilities. - **fblgit/cybertron-v4-qw7B-MGS:** Enhances mathematical reasoning and precision. - **jeffmeloy/Qwen2.5-7B-nerd-uncensored-v1.0:** Provides uncensored technical expertise. - **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. - **Mathematical Reasoning:** Enhanced capability to handle complex computational tasks with high precision, suitable for technical and analytical applications. - **Uncensored Technical Expertise:** Provides robust technical knowledge without content restrictions, making it ideal for specialized technical support and information retrieval. - **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-HomerAnvita-NerdMix** is designed to excel in environments that demand a combination of creative generation, precise instruction following, mathematical reasoning, and technical expertise. 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. - **Mathematical Problem Solving:** Assisting in solving complex mathematical problems and providing step-by-step explanations for educational purposes. - **Technical Documentation and Analysis:** Generating detailed technical documents, reports, and analyses with high precision and clarity. ## 📝 Usage To utilize **ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix**, 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-HomerAnvita-NerdMix" # 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 = "Explain the significance of artificial intelligence in modern healthcare." # 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` - `Anvita` - `Nerd` - `ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix` - `bunnycore/Qandora-2.5-7B-Creative` - `allknowingroger/HomerSlerp1-7B` - `sethuiyer/Qwen2.5-7B-Anvita` - `fblgit/cybertron-v4-qw7B-MGS` - `jeffmeloy/Qwen2.5-7B-nerd-uncensored-v1.0` - `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-HomerAnvita-NerdMix) | Metric |Value| |-------------------|----:| |Avg. |34.17| |IFEval (0-Shot) |77.08| |BBH (3-Shot) |36.58| |MATH Lvl 5 (4-Shot)|29.53| |GPQA (0-shot) | 9.28| |MuSR (0-shot) |14.41| |MMLU-PRO (5-shot) |38.13|