SmolLM
llm-model model
Ultra-small Hugging Face models for edge
Supported languages
SmolLM is a family of ultra-compact language models developed by Hugging Face, with sizes of 135M, 360M, and 1.7B parameters. Designed specifically for edge devices and applications with extreme resource constraints.
Concepts
slmultra-small-modelson-device-aiedge-inferenceparameter-efficiency
Pros and Cons
Ventajas
- + Extremely small (from 135M)
- + Designed by Hugging Face
- + Trained with high-quality data
- + Work on very limited hardware
- + Open source under Apache 2.0
- + Multiple size variants
Desventajas
- - Very basic capabilities
- - Not suitable for complex tasks
- - Limited world knowledge
- - Variable output quality
- - Very short context
Casos de Uso
- Wearable devices
- IoT and smart sensors
- Embedded applications
- Low-end smartphones
- On-device processing