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86613c00e2
* Allow loading images with given std and mean * OpenCLIP text encoder component * Two MobileCLIP models * Clippy fixes. --------- Co-authored-by: Laurent <laurent.mazare@gmail.com>
29 lines
1.1 KiB
Markdown
29 lines
1.1 KiB
Markdown
# candle-mobileclip
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MobileCLIP is family of efficient CLIP-like models using FastViT-based image encoders.
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See [MobileCLIP: Fast Image-Text Models through Multi-Modal Reinforced Training](https://arxiv.org/abs/2311.17049)
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## Running on an example on cpu
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```
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$ cargo run --example mobileclip --release -- --images "candle-examples/examples/stable-diffusion/assets/stable-diffusion-xl.jpg","candle-examples/examples/yolo-v8/assets/bike.jpg" --cpu --sequences "a cycling race","a photo of two cats","a robot holding a candle"
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softmax_image_vec: [2.4819004e-5, 3.81081e-6, 0.9999714, 0.9999738, 2.382714e-5, 2.3317718e-6]
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Results for image: candle-examples/examples/stable-diffusion/assets/stable-diffusion-xl.jpg
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Probability: 0.0025% Text: a cycling race
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Probability: 0.0004% Text: a photo of two cats
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Probability: 99.9971% Text: a robot holding a candle
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Results for image: candle-examples/examples/yolo-v8/assets/bike.jpg
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Probability: 99.9974% Text: a cycling race
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Probability: 0.0024% Text: a photo of two cats
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Probability: 0.0002% Text: a robot holding a candle
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```
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