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#basic openclip usage
import torch
from PIL import Image
import open_clip
mtype='ViT-B-32'
mname='laion2b_s34b_b79k'
print("Loading",mtype,mname)
model, _, preprocess = open_clip.create_model_and_transforms(mtype,
pretrained=mname)
tokenizer = open_clip.get_tokenizer(mtype)
#image = preprocess(Image.open("CLIP.png")).unsqueeze(0)
text = tokenizer(["a diagram", "a dog", "a cat"])
text = tokenizer("cat")
with torch.no_grad(), torch.cuda.amp.autocast():
# image_features = model.encode_image(image)
text_features = model.encode_text(text)
embedding=text_features[0]
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