SmolVLM

An efficient open-source visual language model

CommonProductImageVisual Language ModelMulti-Modal AI

SmolVLM is a compact yet powerful visual language model (VLM) with 2 billion parameters, leading in efficiency and memory usage among similar models. It is fully open-source, with all model checkpoints, VLM datasets, training recipes, and tools released under the Apache 2.0 license. The model is designed for local deployment in browsers or edge devices, reducing inference costs and allowing for user customization.

Supports multi-modal AI for use in smaller local settings.
Completely open-source
allowing for commercial use and custom deployment.
Low memory footprint
suitable for operation on resource-constrained devices.
High performance
with multiple benchmark results including image encoding efficiency.
Supports video analysis tasks
especially in environments with limited computational resources.
Integrates with VLMEvalKit for evaluation across more benchmarks.

\The target audience includes developers and enterprises that need to deploy visual language models on local or edge devices
particularly those sensitive to model size and inference costs. SmolVLM's compact
efficient
and open-source nature makes it well-suited for resource-constrained environments
such as mobile devices or small servers.\

Provide travel recommendations for the Grand Palace in Bangkok using SmolVLM.
Identify areas affected by severe drought based on charts.
Extract due dates and invoice dates from invoices.

1. Visit SmolVLM's Hugging Face page to download the desired model and processor.
2. Load the model and processor using Python and the Transformers library.
3. Prepare input data
including images and text prompts.
4. Format the input data into a model-compatible format using the processor.

Visit

SmolVLM Visit Over Time

Monthly Visits

19075321

Bounce Rate

45.07%

Page per Visit

5.5

Visit Duration

00:05:32

SmolVLM Visit Trend

SmolVLM Visit Geography

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