MatteoKhan
/

MistralGemma-7B-Merged

@@ -1,199 +1,109 @@
 ---
 library_name: transformers
-tags: []
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 ---
+license: mit
+language:
+- en
+base_model:
+- mistralai/Mistral-7B-v0.1
+- google/gemma-7b
 library_name: transformers
+tags:
+- mergekit
+- merged-model
+- mistral
+- gemma
+- language-model
 ---
+# 🚀 MistralGemma-Hybrid-7B: A Fusion of Power & Precision
+## 📌 Overview
+**MistralGemma-Hybrid-7B** is an **experimental hybrid language model** that blends the strengths of **Mistral-7B** and **Gemma-7B** using the **Spherical Linear Interpolation (slerp) merging technique**. Designed to optimize both efficiency and performance, this model offers robust text generation capabilities while leveraging the advantages of both parent models.
+🔗 **Created by**: [Matteo Khan]
+🎓 **Affiliation**: Apprentice at TW3 Partners (Generative AI Research)
+📍 **License**: MIT
+🔗 [Connect with me on LinkedIn](https://www.linkedin.com/in/matteo-khan-a10309263/)
+🔗 [Model on Hugging Face](https://huggingface.co/YourProfile/MistralGemma-Hybrid-7B)
+## 🧠 Model Details
+- **Model Type**: Hybrid Language Model (Merged)
+- **Parent Models**:
+  - [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)
+  - [Gemma-7B](https://huggingface.co/google/gemma-7b)
+- **Merging Technique**: Slerp Merge (MergeKit)
+## 🎯 Intended Use
+This model is intended for **research and experimentation** in hybrid model optimization. Potential applications include:
+- ✅ Text Generation
+- ✅ Conversational AI
+- ✅ Creative Writing Assistance
+- ✅ Exploration of Model Merging Effects
+## ⚠️ Limitations & Considerations
+While **MistralGemma-Hybrid-7B** offers enhanced capabilities, it also inherits limitations from its parent models:
+- ❌ May generate **inaccurate or misleading** information
+- ⚠️ Potential for **biased, offensive, or harmful** content
+- 🔄 Merging may introduce **unpredictable behaviors**
+- 📉 Performance may **vary across different tasks**
+## 🔬 Merging Process & Configuration
+This is **not a newly trained model**, but rather a merge of existing models using the following configuration:
+```yaml
+merge_method: slerp  # Using slerp instead of linear
+dtype: float16
+models:
+  - model: "mistralai/Mistral-7B-v0.1"
+    parameters:
+      weight: 0.5
+  - model: "google/gemma-7b"
+    parameters:
+      weight: 0.5
+parameters:
+  normalize: true
+  int8_mask: false
+  rescale: true  # Helps with different model scales
+layers:
+  - pattern: ".*"
+    layer_range: [0, -1]
+```
+📊 **No formal evaluation** has been conducted yet. Users are encouraged to **benchmark and share feedback**!
+## 🌍 Environmental Impact
+By utilizing **model merging** rather than training from scratch, **MistralGemma-Hybrid-7B** significantly reduces computational and environmental costs.
+## 🚀 How to Use
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+model_name = "YourProfile/MistralGemma-Hybrid-7B"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+# Example usage
+prompt = "Write a short story about the future of AI."
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_length=200)
+response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+print(response)
+```
+**📝 Citation**
+```bibtex
+@misc{mistralgemma2025,
+      title={MistralGemma: A Hybrid Open-Source Language Model},
+      author={Your Name},
+      year={2025},
+      eprint={arXiv:XXXX.XXXXX},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```
+📩 **Feedback & Contact**: Reach out via [Hugging Face](https://huggingface.co/YourProfile).
+🎉 **Happy Experimenting!** 🚀