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DeeperML
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Hugging Face has unveiled two new compact AI models, SmolVLM-256M and SmolVLM-500M, designed to analyze images, short videos, and text on devices with limited resources. These models, requiring less than 1GB of RAM, are intended for use in constrained environments where computational power is scarce, such as laptops with limited RAM. The models are not only small in size, but also in parameter count, with 256 million and 500 million parameters, respectively. The team states that they are ideal for developers looking to process large amounts of data very cheaply.
These new models can perform tasks like describing images or video clips and answering questions about PDFs, including scanned text and charts. Hugging Face used datasets called The Cauldron, a collection of 50 high-quality image and text datasets, and Docmatix, a set of file scans paired with detailed captions, to train SmolVLM-256M and SmolVLM-500M. The company also claims that SmolVLM-256M and SmolVLM-500M outperform the larger Idefics 80B model on benchmarks such as AI2D, which evaluates the ability to analyze science diagrams. The models are available on the web and for download with an Apache 2.0 license.
ImgSrc: d15shllkswkct0.
References :
These new models can perform tasks like describing images or video clips and answering questions about PDFs, including scanned text and charts. Hugging Face used datasets called The Cauldron, a collection of 50 high-quality image and text datasets, and Docmatix, a set of file scans paired with detailed captions, to train SmolVLM-256M and SmolVLM-500M. The company also claims that SmolVLM-256M and SmolVLM-500M outperform the larger Idefics 80B model on benchmarks such as AI2D, which evaluates the ability to analyze science diagrams. The models are available on the web and for download with an Apache 2.0 license.
ImgSrc: d15shllkswkct0.
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References :
- www.techmeme.com: Hugging Face releases SmolVLM-256M and SmolVLM-500M, claiming they can analyze images, short videos, and text on "constrained devices" with under ~1GB of RAM (Kyle Wiggers/TechCrunch)
- siliconangle.com: Hugging Face open-sources world’s smallest vision language model
- techcrunch.com: Hugging Face releases SmolVLM-256M and SmolVLM-500M, claiming they can analyze images, short videos, and text on "constrained devices" with under ~1GB of RAM (Kyle Wiggers/TechCrunch)
- Techmeme: Hugging Face releases SmolVLM-256M and SmolVLM-500M, claiming they can analyze images, short videos, and text on "constrained devices" with under ~1GB of RAM
- SiliconANGLE: Hugging Face open-sources world’s smallest vision language model
Classification:
- HashTags: #HuggingFace #AIModels #EdgeAI
- Company: Hugging Face
- Product: SmolVLM
- Feature: image analysis
- Type: AI
- Severity: Informative