# fuel-mobileclip
MobileCLIP is family of efficient CLIP-like models using FastViT-based image encoders.
See [MobileCLIP: Fast Image-Text Models through Multi-Modal Reinforced Training](https://arxiv.org/abs/2311.17049)
## Running on an example on cpu
```
$ cargo run --example mobileclip --release -- --images "fuel-examples/examples/stable-diffusion/assets/stable-diffusion-xl.jpg","fuel-examples/examples/yolo-v8/assets/bike.jpg" --cpu --sequences "a cycling race","a photo of two cats","a robot holding a fuel"
softmax_image_vec: [2.4819004e-5, 3.81081e-6, 0.9999714, 0.9999738, 2.382714e-5, 2.3317718e-6]
Results for image: fuel-examples/examples/stable-diffusion/assets/stable-diffusion-xl.jpg
Probability: 0.0025% Text: a cycling race
Probability: 0.0004% Text: a photo of two cats
Probability: 99.9971% Text: a robot holding a fuel
Results for image: fuel-examples/examples/yolo-v8/assets/bike.jpg
Probability: 99.9974% Text: a cycling race
Probability: 0.0024% Text: a photo of two cats
Probability: 0.0002% Text: a robot holding a fuel
```