SILMA-9B-Instruct-v1.0
| Property | Value |
|---|---|
| Parameter Count | 9.24B |
| Model Type | Instruction-tuned Language Model |
| License | Gemma |
| Tensor Type | BF16 |
| Languages | Arabic, English |
What is SILMA-9B-Instruct-v1.0?
SILMA-9B-Instruct-v1.0 is a state-of-the-art bilingual language model developed by SILMA.AI, built on Google's Gemma architecture. Despite its relatively modest 9B parameter size, it achieves remarkable performance in Arabic language tasks, outperforming models up to 72B parameters in size. This makes it particularly efficient for practical business applications while maintaining high performance.
Implementation Details
The model is implemented using the Transformers library and supports various deployment options, including standard GPU inference, 8-bit and 4-bit quantization, and optimization through Torch compile. It requires minimum 16GB GPU memory when quantized, with recommended specs of 48GB for optimal performance.
- Built on Google Gemma architecture
- Supports both CPU and GPU inference
- Multiple quantization options available
- Customizable chat template for conversations
Core Capabilities
- Bilingual proficiency in Arabic and English
- Strong performance in Arabic language benchmarks (e.g., 71.85% on AlGhafa benchmark)
- Text generation and conversation
- Code generation capabilities
- Question answering and knowledge tasks
Frequently Asked Questions
Q: What makes this model unique?
SILMA-9B stands out for achieving top performance in Arabic language tasks despite being significantly smaller than competitors, making it more practical for deployment while maintaining high accuracy.
Q: What are the recommended use cases?
The model excels in content creation, chatbots, text summarization, research applications, and educational tools, particularly for Arabic language applications. It's especially suited for businesses requiring efficient Arabic language processing.
