---
license: mit
language:
- en
base_model:
- cerebras/Cerebras-GPT-6.7B
- facebook/opt-6.7b
library_name: transformers
tags:
- mergekit
- merged-model
- cerebras
- opt
- language-model
---

# 🚀 CerebrasOPT-Hybrid-6.7B: A Balanced Fusion of Strength & Efficiency

## 📌 Overview
**CerebrasOPT-Hybrid-6.7B** is an **experimental hybrid language model** that merges the capabilities of **Cerebras-GPT-6.7B** and **OPT-6.7B** using the **Linear Merge technique**. This approach aims to enhance performance while maintaining efficiency, leveraging the best 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 HF中国镜像站](https://huggingface.co/YourProfile/CerebrasOPT-Hybrid-6.7B)  

## 🧠 Model Details
- **Model Type**: Hybrid Language Model (Merged)
- **Parent Models**:
  - [Cerebras-GPT-6.7B](https://huggingface.co/cerebras/Cerebras-GPT-6.7B)
  - [OPT-6.7B](https://huggingface.co/facebook/opt-6.7b)
- **Merging Technique**: Linear Merge (MergeKit)

## 🎯 Intended Use
This model is primarily intended for **research and experimentation** in hybrid model optimization. Possible applications include:
- ✅ Text Generation
- ✅ Conversational AI
- ✅ Creative Writing Assistance
- ✅ Exploration of Model Merging Effects

## ⚠️ Limitations & Considerations
While **CerebrasOPT-Hybrid-6.7B** provides enhanced capabilities, it also inherits certain 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: linear
dtype: float16
models:
  - model: "cerebras/Cerebras-GPT-6.7B"
    parameters:
      t: 1.0
      weight: 0.5
  - model: "facebook/opt-6.7b"
    parameters:
      t: 1.0
      weight: 0.5

parameters:
  normalize: true
  int8_mask: false

layers:
  - pattern: "model.*"
```

📊 **No formal evaluation** has been conducted yet. Users are encouraged to **benchmark and share feedback**!

## 🌍 Environmental Impact
By utilizing **model merging** instead of training from scratch, **CerebrasOPT-Hybrid-6.7B** significantly reduces computational and environmental costs.

## 🚀 How to Use
```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "YourProfile/CerebrasOPT-Hybrid-6.7B"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# Example usage
prompt = "Describe the future of AI in a short paragraph."
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{cerebrasopt2025,
      title={CerebrasOPT: 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 [HF中国镜像站](https://huggingface.co/YourProfile).

🎉 **Happy Experimenting!** 🚀