Hugging Face’s SmolVLM could cut AI costs for ... - VentureBeat
3 days ago · Hugging Face launches SmolVLM, a compact and efficient vision-language AI model, offering businesses a cost-effective solution for advanced AI implementation without sacrificing performance.
Hugging Face Unveils SmolVLM, Visual Language AI For the Edge
3 days ago · Hugging Face unveils SmolVLM, a 2B parameter vision-language model optimized for on-device AI, offering efficiency, customization, and open-source tools.
blog/smolvlm.md at main · huggingface/blog · GitHub
SmolVLM is small, fast, memory-efficient, and fully open-source. All model checkpoints, VLM datasets, training recipes and tools are released under the Apache 2.0 license. What is …
Hugging Face Releases SmolVLM: A 2B Parameter Vision …
5 days ago · Hugging Face recently released SmolVLM, a 2B parameter vision-language model specifically designed for on-device inference. SmolVLM outperforms other models with comparable GPU RAM usage and token throughput.
Hugging Face model SmolVLM requires a lot less compute
2 days ago · For SmolVLM, Hugging Face significantly modified the architecture, resulting in a model that requires 5.02 GB of RAM. For example, this is significantly less than InternVL2 2B, which requires 10.52 GB of memory. This more efficient approach makes SmolVLM suitable for on-device applications, with the model continuing to deliver strong performance.
Hugging Face Launches 2B Parameter Visual Language Model SmolVLM…
4 days ago · 🌟 SmolVLM is a 2B parameter visual language model launched by Hugging Face, designed for on-device inference, running efficiently without high-end hardware. ⚡ Its token generation speed is 7.5 to 16 times faster than similar models, greatly enhancing user experience and application efficiency.
New AI model from Hugging Face promises efficient image …
4 days ago · Hugging Face has introduced SmolVLM, a new vision-language AI model that processes both images and text while using significantly less computing power than comparable solutions. As reported by Michael Nuñez, the model requires only 5.02 GB of GPU RAM, compared to competitors that need up to 13.70 GB.
SmolVLM - small yet mighty Vision Language Model
2 days ago · SmolVLM is small, fast, memory-efficient, and fully open-source. All model checkpoints, VLM datasets, training recipes and tools are released under the Apache 2.0 license. I've tried it in a few flavours but my favourite so far is the mlx-vlm approach, via mlx-vlm author Prince Canuma .
@merve on Hugging Face: "Small yet mighty! We are releasing SmolVLM …
We are releasing SmolVLM: a new 2B small vision language made for on-device use, fine-tunable on consumer GPU, immensely memory efficient 🤠 We release three checkpoints under Apache 2.0: SmolVLM-Instruct, SmolVLM-Synthetic and SmolVLM-Base HuggingFaceTB/smolvlm-6740bd584b2dcbf51ecb1f39
GitHub - huggingface/smollm: Everything about the SmolLM
New: Introducing SmolVLM, a Vision Language Model using SmolLM2 as a language backbone 🚀