---
license: apache-2.0
base_model:
- TinyLlama/TinyLlama-1.1B-step-50K-105b
- TinyLlama/TinyLlama-1.1B-Chat-v1.0
tags:
- merge
- mergekit
- tinyllama
- slerp
---
# TinyLlama-Hybrid-Merge
This is a merge of TinyLlama models created using MergeKit, combining the foundational capabilities of the base TinyLlama with its Chat-tuned version through a sophisticated SLERP fusion with variable interpolation values.

## About Me
I'm David Soeiro-Vuong, a third-year Computer Science student working as an apprentice at TW3 Partners, a company specialized in Generative AI. Passionate about artificial intelligence and language models optimization, I focus on creating efficient model merges that balance performance and capabilities.

🔗 [Connect with me on LinkedIn](https://www.linkedin.com/in/david-soeiro-vuong-a28b582ba/)

## Merge Details
### Merge Method
This model uses SLERP (Spherical Linear Interpolation) with carefully tuned parameters to achieve optimal performance balance:

- **Attention Layers**: Variable interpolation values [0, 0.5, 0.3, 0.7, 1] leveraging the chat model's instruction-following capabilities
- **MLP Layers**: Variable interpolation values [1, 0.5, 0.7, 0.3, 0] maintaining the base model's reasoning capabilities
- **Other Parameters**: 0.5 interpolation value creating an equal blend for balanced performance
- **Format**: bfloat16 precision for efficient memory usage

### Models Merged
* [TinyLlama/TinyLlama-1.1B-step-50K-105b](https://huggingface.co/TinyLlama/TinyLlama-1.1B-step-50K-105b) - The base TinyLlama model offering foundational language capabilities
* [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) - A fine-tuned version optimized for chat and instruction following

### Configuration
```yaml
slices:
  - sources:
      - model: TinyLlama/TinyLlama-1.1B-step-50K-105b
        layer_range: [0, 22]
      - model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
        layer_range: [0, 22]
merge_method: slerp
base_model: TinyLlama/TinyLlama-1.1B-step-50K-105b
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
dtype: bfloat16
```

## Model Capabilities
This merge combines:
- TinyLlama base model's foundational knowledge and reasoning
- TinyLlama Chat's improved instruction following and conversational abilities
- Optimized parameter distribution for balanced performance
- Compact 1.1B parameter size suitable for resource-constrained environments

The resulting model provides enhanced performance on tasks requiring both reasoning and conversational abilities, such as:
- Basic question answering with improved coherence
- Simple instruction following with better response quality
- Lightweight deployment scenarios requiring balanced capabilities
- Educational and demonstration purposes for model merging techniques

## Limitations
- Inherits the fundamental limitations of small 1.1B parameter models
- Limited context window and knowledge compared to larger models
- May struggle with complex reasoning, specialized domains, or nuanced tasks
- No additional training beyond the parameter merging process
- Performance ceiling constrained by the small model size

## License
This model is released under the Apache 2.0 license, consistent with the underlying models' licenses.