"Now, we are taking the next step: running the SmolVLM model directly in the browser using Transformers.js, Next.js, and Tailwind CSS. This tutorial will guide you step by step, with a detailed breakdown of every line of code and the reasoning behind it. By the end, you will have a browser-based multimodal chatbot that understands images and text simultaneously, all running locally without a backend."
"To learn how to run the SmolVLM model on your browser, just keep reading. Would you like immediate access to 3,457 images curated and labeled with hand gestures to train, explore, and experiment with ... for free? Head over to Roboflow and get a free account to grab these hand gesture images. Need Help Configuring Your Development Environment? Having trouble configuring your development environment? Want access to pre-configured Jupyter Notebooks running on Google Colab?"
SmolVLM can run directly in the browser using Transformers.js, Next.js, and Tailwind CSS without requiring a backend. The setup produces a browser-based multimodal chatbot capable of understanding images and text at the same time. The workflow includes detailed, line-by-line code explanations and reasoning to implement the model locally. SmolVLM supports multi-image understanding and can power highlight-reel generation from long-duration videos with a Gradio interface. A curated set of 3,457 hand-gesture images is available via Roboflow for training and experimentation. Pre-configured Jupyter Notebooks on Google Colab are available for immediate environment setup and execution.
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