Model reference · open weights
SmolVLM2-Video is an open-weight language model from HuggingFaceTB, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.
About
SmolVLM2-500M-Video SmolVLM2-500M-Video is a lightweight multimodal model designed to analyze video content. The model processes videos, images, and text inputs to generate text outputs - whether answering questions about media files, comparing visual content, or transcribing text from images. Despite its compact size, requiring only 1.8GB of GPU RAM for video inference, it delivers robust performance on complex multimodal tasks. This efficiency makes it particularly well-suited for on-device applications where computational resources may be limited. Model Summary - Developed by: Hugging Face 🤗 - Model type: Multi-modal model (image/multi-image/video/text) - Language(s) (NLP): English - License: Apache 2.0 - Architecture: Based on Idefics3 (see technical summary) Resources - Demo: Video Highlight Generator - Blog: Blog post Uses SmolVLM2 can be used for inference on multimodal (video / image / text) tasks where the input consists of text queries along with video or one or more images. Text and media files can be interleaved arbitrarily, enabling tasks like captioning, visual question answering, and storytelling based on visual content. The model does not support image or video generation. To fine-tune SmolVLM2 on a specific task, you can follow the fine-tuning tutorial. Evaluation We evaluated the performance of the SmolVLM2 family on the following scientific benchmarks: How to get started You can use transformers to load, infer and fine-tune SmolVLM. Make sure you have num2words, flash-attn and latest transformers installed. You can load the model as follows. Simple Inference You preprocess your inputs directly using chat templates and directly passing them Video Inference To use SmolVLM2 for video inference, make sure you have decord installed. Multi-image Interleaved Inference You can interleave multiple media with text using chat templates. Model optimizations Misuse and Out-of-scope Use SmolVLM is not intended for high-stakes scenarios or critical decision-making processes that affect an individual's well-being or livelihood. The model may produce content that appears factual but may not be accurate. Misuse includes, but is not limited to: - Prohibited Uses
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | HuggingFaceTB |
|---|---|
| Type | Language models |
| Parameters (lead) | 507M |
| Variants | 2 |
| Runs with | transformers |
| Based on | HuggingFaceTB/SmolVLM-500M-Instruct |
| Released | 2025-02-11 |
| Popularity | 1.5M downloads / month |
| Likes | 173 |
| Licence | Open weights |
How it works
Variants
Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.
Using it via the API
Once AxForge deploys smolvlm2-video for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (smolvlm2-video below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/chat/completions \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"smolvlm2-video","messages":[{"role":"user","content":"Hello"}]}'
Licence
Open weights under apache-2.0 — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗
Sources