Captain-Eris_Violet-V0.420-12B
| Property | Value |
|---|---|
| Model Size | 12B parameters |
| Quantization | 4-bit (4bpw-exl2) |
| Base Models | Captain_BMO-12B, Violet_Twilight-v0.2 |
| Author | Nitral-AI |
| Model URL | Hugging Face |
What is Captain-Eris_Violet-V0.420-12B?
Captain-Eris_Violet is a sophisticated merged language model that combines the capabilities of Captain_BMO-12B and Violet_Twilight-v0.2 using advanced SLERP (Spherical Linear Interpolation) merging techniques. The model features custom-tuned interpolation weights for both attention and MLP layers, optimized for enhanced performance.
Implementation Details
The model employs a complex merging strategy using layer-specific interpolation values. The attention layers use varying interpolation weights [0, 0.5, 0.3, 0.7, 1], while MLP layers use complementary weights [1, 0.5, 0.7, 0.3, 0]. The overall interpolation parameter (t) is set to 0.420, and the model uses bfloat16 precision.
- 4-bit quantization using exl2 format
- ARM-compatible GGUF format available
- 40-layer architecture from both parent models
- Custom SLERP merge configuration
Core Capabilities
- Efficient deployment through 4-bit quantization
- Balanced performance through carefully tuned layer merging
- Cross-platform compatibility (including ARM)
- Optimized memory usage while maintaining model quality
Frequently Asked Questions
Q: What makes this model unique?
The model's uniqueness lies in its sophisticated merging strategy, using varying interpolation weights across different layer types, combined with efficient 4-bit quantization for practical deployment.
Q: What are the recommended use cases?
The model is suitable for applications requiring efficient deployment of large language models, particularly in scenarios where memory optimization is crucial while maintaining model capabilities.
