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# Efficient Visual Question Answering
Qwen2.5 VL 3B Instruct GPTQ Int3
Apache-2.0
The GPTQ-Int3 quantized version of Qwen2.5-VL-3B-Instruct, suitable for multimodal image-text processing tasks with reduced VRAM usage and faster inference speed.
Image-to-Text
Transformers Supports Multiple Languages
Transformers Supports Multiple LanguagesQ
hfl
60
1
Nanollava 1.5
Apache-2.0
nanoLLaVA-1.5 is a vision-language model with under 1 billion parameters, designed specifically for edge devices—compact yet powerful.
Image-to-Text Transformers English
Transformers EnglishN
qnguyen3
442
109
Imp V1.5 4B Phi3
Apache-2.0
Imp-v1.5-4B-Phi3 is a high-performance lightweight multimodal large model with only 4 billion parameters, built on the Phi-3 framework and SigLIP visual encoder.
Text-to-Image Transformers
TransformersI
MILVLG
140
7
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