SmolVLM - AI Image Models Tool

Overview

SmolVLM is a 2B-parameter vision-language model designed to be small, fast, and memory-efficient. It extends the Idefics3 architecture with improved visual compression and optimized patch processing to support local deployment, including on laptops. All model checkpoints, training recipes, and tools are released open-source under the Apache 2.0 license.

Key Features

• 2B-parameter vision-language model
• Small, fast, memory-efficient design for local inference
• Improved visual compression strategy for efficient image encoding
• Optimized patch processing to reduce compute and memory overhead
• Builds on the Idefics3 architecture with targeted modifications
• Model checkpoints, recipes, and tools released under Apache 2.0

Ideal Use Cases

• On-device visual understanding and inference on laptops
• Research and experimentation with vision-language models
• Fine-tuning or adapting the model using provided recipes
• Prototyping multimodal features for lightweight applications
• Edge deployment where memory and latency are constrained

Getting Started

• Open the SmolVLM blog page on Hugging Face.
• Read the model description, license, and available artifacts.
• Download or clone model checkpoints and training recipes.
• Follow the provided training recipes or example scripts.
• Run inference locally using the included tools and checkpoints.

Pricing

No pricing disclosed. Model checkpoints and tools are released open-source under the Apache 2.0 license.

Key Information

• Category: Image Models
• Type: AI Image Models Tool