FemtoVLM is the smallest visual question answering/captioning model in the world. It accepts image and text inputs to produce text outputs. It's designed for efficiency. FemtoVLM can answer questions about images and describe visual content. Its lightweight architecture makes it suitable for on-device applications while maintaining strong performance.

FemtoVLM comes in three sizes: 116M (femto), 143M (tiny), 160M (base), 225M (dino). All models are trained for image captioning and question answering in real-world contexts. FemtoVLM cannot perform optical character recognition (OCR), multi-turn question-answering, or scientific question answering.

Setup

bash

pip install git+https://github.com/facebookresearch/schedule_free.git
pip install peft
git clone https://github.com/mkturkcan/seers.git
cd seers/seers/
git clone https://huggingface.co/mehmetkeremturkcan/FemtoVLM-Small

Test

Run, in the seers/seers folder,

python femtovlm_inference.py

Train

seers training code is public! Run

python femtovlm_train.py