Overview
Small language models, typically ranging from 1 billion to 7 billion parameters, offer a good balance between performance and resource requirements.
Key Characteristics
Advantages
- Lower resource requirements
- Faster inference times
- Easier deployment
- Lower costs
Limitations
- Limited context understanding
- Less capable of complex reasoning
- May struggle with nuanced tasks
- Lower quality outputs
Popular Models
| Model | Parameters | Use Cases | Hardware Requirements |
|---|---|---|---|
| GPT-2 Small | 117M | Text generation, basic tasks | CPU or basic GPU |
| BLOOM-1B7 | 1.7B | Multilingual tasks | Mid-range GPU |
| T5 Small | 60M | Text-to-text tasks | CPU or basic GPU |
Best Use Cases
- Basic text generation
- Simple classification tasks
- Resource-constrained environments
- Edge devices and mobile applications