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---
license: apache-2.0
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
language:
- en
library_name: transformers
---
# 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`
--- |