Update README.md

README.md

@@ -6,15 +6,23 @@ tags:
 - lazymergekit
 - bunnycore/QandoraExp-7B
 - trollek/Qwen2.5-7B-CySecButler-v0.1
+base_model:
+- bunnycore/QandoraExp-7B
+- trollek/Qwen2.5-7B-CySecButler-v0.1
+library_name: transformers
 ---
+# Qwen2.5-7B-Qandora-CySec
+
+ZeroXClem/Qwen2.5-7B-Qandora-CySec is an advanced model merge combining Q&A capabilities and cybersecurity expertise using the mergekit framework. This model excels in both general question-answering tasks and specialized cybersecurity domains.
 
-# ZeroXClem/Qwen2.5-7B-Qandora-CySec
+## 🚀 Model Components
 
-ZeroXClem/Qwen2.5-7B-Qandora-CySec is a merge of the following models using [mergekit](https://github.com/cg123/mergekit):
-* [bunnycore/QandoraExp-7B](https://huggingface.co/bunnycore/QandoraExp-7B)
-* [trollek/Qwen2.5-7B-CySecButler-v0.1](https://huggingface.co/trollek/Qwen2.5-7B-CySecButler-v0.1)
+- **[bunnycore/QandoraExp-7B](https://huggingface.co/bunnycore/QandoraExp-7B)**: Powerful Q&A capabilities
+- **[trollek/Qwen2.5-7B-CySecButler-v0.1](https://huggingface.co/trollek/Qwen2.5-7B-CySecButler-v0.1)**: Specialized cybersecurity knowledge
 
-## 🧩 Configuration
+## 🧩 Merge Configuration
+
+The models are merged using spherical linear interpolation (SLERP) for optimal blending:
 
 ```yaml
 slices:
@@ -33,5 +41,51 @@ parameters:
       value: [1, 0.5, 0.7, 0.3, 0]
     - value: 0.5
 dtype: bfloat16
+```
+
+### Key Parameters
+
+- **Self-Attention (self_attn)**: Controls blending across self-attention layers
+- **MLP**: Adjusts Multi-Layer Perceptron balance
+- **Global Weight (t.value)**: 0.5 for equal contribution from both models
+- **Data Type**: bfloat16 for efficiency and precision
+
+## 🎯 Applications
+
+1. General Q&A Tasks
+2. Cybersecurity Analysis
+3. Hybrid Scenarios (general knowledge + cybersecurity)
+
+## 🛠 Usage
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model_name = "ZeroXClem/Qwen2.5-7B-Qandora-CySec"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+input_text = "What are the fundamentals of python programming?"
+input_ids = tokenizer.encode(input_text, return_tensors="pt")
+output = model.generate(input_ids, max_length=100)
+response = tokenizer.decode(output[0], skip_special_tokens=True)
+print(response)
+```
+
+## 📜 License
+
+This model inherits the licenses of its base models. Refer to bunnycore/QandoraExp-7B and trollek/Qwen2.5-7B-CySecButler-v0.1 for usage terms.
+
+## 🙏 Acknowledgements
+
+- bunnycore (QandoraExp-7B)
+- trollek (Qwen2.5-7B-CySecButler-v0.1)
+- mergekit project
+
+## 📚 Citation
+
+If you use this model, please cite this repository and the original base models.
+
+## 💡 Tags
 
-```
+merge, mergekit, lazymergekit, bunnycore/QandoraExp-7B, trollek/Qwen2.5-7B-CySecButler-v0.1, cybersecurity, Q&A