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README.md
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- merge
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- mergekit
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- lazymergekit
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---
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# ZeroXClem/Qwen2.5-7B-HomerCreative-Mix
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ZeroXClem/Qwen2.5-7B-HomerCreative-Mix is
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##
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```yaml
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# Merge configuration for ZeroXClem/Qwen2.5-7B-HomerCreative-Mix using Model Stock
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normalize: false
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int8_mask: true
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dtype: bfloat16
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-
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- merge
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- mergekit
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- lazymergekit
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- creative
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- roleplay
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- instruct
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- qwen
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- model_stock
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- bfloat16
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base_model:
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- newsbang/Homer-v0.5-Qwen2.5-7B
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- allknowingroger/HomerSlerp1-7B
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- bunnycore/Qwen2.5-7B-Instruct-Fusion
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- bunnycore/Qandora-2.5-7B-Creative
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language:
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- en
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library_name: transformers
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---
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# ZeroXClem/Qwen2.5-7B-HomerCreative-Mix
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**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.
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## π Merged Models
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This model merge incorporates the following:
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- [**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.
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- [**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.
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- [**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.
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- [**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.
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## 𧩠Merge Configuration
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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.
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```yaml
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# Merge configuration for ZeroXClem/Qwen2.5-7B-HomerCreative-Mix using Model Stock
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normalize: false
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int8_mask: true
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dtype: bfloat16
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```
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### Key Parameters
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- **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.
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- **Models (`models`):** Specifies the list of models to be merged:
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- **bunnycore/Qandora-2.5-7B-Creative:** Enhances creative text generation.
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- **bunnycore/Qwen2.5-7B-Instruct-Fusion:** Improves instruction-following capabilities.
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- **allknowingroger/HomerSlerp1-7B:** Facilitates smooth blending of model weights using SLERP.
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- **Base Model (`base_model`):** Defines the foundational model for the merge, which is **newsbang/Homer-v0.5-Qwen2.5-7B** in this case.
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- **Normalization (`normalize`):** Set to `false` to retain the original scaling of the model weights during the merge.
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- **INT8 Mask (`int8_mask`):** Enabled (`true`) to apply INT8 quantization masking, optimizing the model for efficient inference without significant loss in precision.
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- **Data Type (`dtype`):** Uses `bfloat16` to maintain computational efficiency while ensuring high precision.
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## π Performance Highlights
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- **Creative Text Generation:** Enhanced ability to produce imaginative and diverse content suitable for creative writing, storytelling, and content creation.
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- **Instruction Following:** Improved performance in understanding and executing user instructions, making the model more responsive and accurate in task execution.
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- **Optimized Inference:** INT8 masking and `bfloat16` data type contribute to efficient computation, enabling faster response times without compromising quality.
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## π― Use Case & Applications
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**ZeroXClem/Qwen2.5-7B-HomerCreative-Mix** is designed to excel in environments that demand both creative generation and precise instruction following. Ideal applications include:
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- **Creative Writing Assistance:** Aiding authors and content creators in generating imaginative narratives, dialogues, and descriptive text.
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- **Interactive Storytelling and Role-Playing:** Enhancing dynamic and engaging interactions in role-playing games and interactive storytelling platforms.
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- **Educational Tools and Tutoring Systems:** Providing detailed explanations, answering questions, and assisting in educational content creation with contextual understanding.
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- **Technical Support and Customer Service:** Offering accurate and contextually relevant responses in technical support scenarios, improving user satisfaction.
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- **Content Generation for Marketing:** Creating compelling and diverse marketing copy, social media posts, and promotional material with creative flair.
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## π Usage
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To utilize **ZeroXClem/Qwen2.5-7B-HomerCreative-Mix**, follow the steps below:
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### Installation
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First, install the necessary libraries:
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```bash
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pip install -qU transformers accelerate
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```
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### Example Code
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Below is an example of how to load and use the model for text generation:
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
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import torch
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# Define the model name
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model_name = "ZeroXClem/Qwen2.5-7B-HomerCreative-Mix"
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# Load the tokenizer
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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# Load the model
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model = AutoModelForCausalLM.from_pretrained(
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model_name,
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torch_dtype=torch.bfloat16,
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device_map="auto"
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)
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# Initialize the pipeline
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text_generator = pipeline(
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"text-generation",
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model=model,
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tokenizer=tokenizer,
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torch_dtype=torch.bfloat16,
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device_map="auto"
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)
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# Define the input prompt
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prompt = "Once upon a time in a land far, far away,"
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# Generate the output
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outputs = text_generator(
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prompt,
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max_new_tokens=150,
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do_sample=True,
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temperature=0.7,
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top_k=50,
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top_p=0.95
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)
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# Print the generated text
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print(outputs[0]["generated_text"])
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```
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### Notes
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- **Fine-Tuning:** This merged model may require fine-tuning to optimize performance for specific applications or domains.
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- **Resource Requirements:** Ensure that your environment has sufficient computational resources, especially GPU-enabled hardware, to handle the model efficiently during inference.
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- **Customization:** Users can adjust parameters such as `temperature`, `top_k`, and `top_p` to control the creativity and diversity of the generated text.
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## π License
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This model is open-sourced under the **Apache-2.0 License**.
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## π‘ Tags
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- `merge`
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- `mergekit`
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- `model_stock`
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- `Qwen`
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- `Homer`
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- `Creative`
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- `ZeroXClem/Qwen2.5-7B-HomerCreative-Mix`
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- `bunnycore/Qandora-2.5-7B-Creative`
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- `bunnycore/Qwen2.5-7B-Instruct-Fusion`
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- `allknowingroger/HomerSlerp1-7B`
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- `newsbang/Homer-v0.5-Qwen2.5-7B`
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---
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