CLIP and SigLIP models optimized with TensorRT with a Transformers-like API
python3 -m clip_trt \
--inputs image_a.jpg image_b.jpg image_c.jpg \
--inputs 'a dog' 'a cat' 'a bear' 'a lion'from clip_trt import CLIPModel
model = CLIPModel.from_pretrained(
"openai/clip-vit-large-patch14-336",
use_tensorrt=True,
crop=False,
)
similarity = model(
[
'my_image.jpg',
PIL.Image.open('image_2.jpg').convert('RGB'),
np.ndarray((3,480,640), dtype=np.uint8),
torch.ones((3,336,336), dtype=torch.uint8, device='cuda')
],
[
'a dog', 'a cat', 'a bear', 'a lion'
],
)image_embed = model.embed('xyz.jpg')
text_embed = model.embed('an elephant in the jungle')