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SmolVLM2-256M-Video-Instruct-ternary
AsadIsmail/SmolVLM2-256M-Video-Instruct-ternary
SmolVLM2-256M-Video-Instruct-ternary is a image-text-to-text model from AsadIsmail. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
Ternary-quantized version of HuggingFaceTB/SmolVLM2-256M-Video-Instruct — the smallest video-understanding VLM, now even smaller. Ideal for edge deployment.
Access
Public
Updated Apr 17, 2026
Repo size
128 MB
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0
Public
Repo makeup
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.npz128 MB · 100%
At a glance
- Task
- Image-Text-to-Text
- Library
- transformers
- License
- apache-2.0
- Access
- Public
- Created
- Apr 17, 2026
- Updated
- Apr 17, 2026
- SHA
- cae63f7d
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Base models
Model card
From the Hugging Face model README
SmolVLM2-256M-Video-Instruct — Ternary Quantized (tritplane3)
Ternary-quantized version of HuggingFaceTB/SmolVLM2-256M-Video-Instruct — the smallest video-understanding VLM, now even smaller. Ideal for edge deployment.
Specifications
| Property | Value |
|---|---|
| Base Model | HuggingFaceTB/SmolVLM2-256M-Video-Instruct |
| Parameters | 256M |
| Quantization | tritplane3 (211 linear layers) |
| Full-model effective bits | 12.91 |
| Compression ratio | 1.24× |
| Avg reconstruction error | 0.1488 |
Collection
Part of ternary-models.
- Task
- Image-Text-to-Text
- Library
- transformers
- License
- apache-2.0
- Languages
- en
- Created
- Apr 17, 2026
- Updated
- Apr 17, 2026