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[0, 20000)
are image tokens.[20000, 20100)
are common tokens, mainly punctuations. E.g., icetk[20000] == '<unk>'
, icetk[20003] == '<pad>'
, icetk[20006] == ','
.[20100, 83823)
are English tokens.[83823, 145653)
are Chinese tokens.[145653, 150000)
are rare tokens. E.g., icetk[145803] == 'α'
.You can install the package via
pip install icetk
from icetk import icetk
tokens = icetk.tokenize('Hello World! I am icetk.')
# tokens == ['▁Hello', '▁World', '!', '▁I', '▁am', '▁ice', 'tk', '.']
ids = icetk.encode('Hello World! I am icetk.')
# ids == [39316, 20932, 20035, 20115, 20344, 22881, 35955, 20007]
en = icetk.decode(ids)
# en == 'Hello World! I am icetk.' # always perfectly recover (if without <unk>)
ids = icetk.encode('你好世界!这里是 icetk。')
# ids == [20005, 94874, 84097, 20035, 94947, 22881, 35955, 83823]
ids = icetk.encode(image_path='test.jpeg', image_size=256, compress_rate=8)
# ids == tensor([[12738, 12430, 10398, ..., 7236, 12844, 12386]], device='cuda:0')
# ids.shape == torch.Size([1, 1024])
img = icetk.decode(image_ids=ids, compress_rate=8)
# img.shape == torch.Size([1, 3, 256, 256])
from torchvision.utils import save_image
save_image(img, 'recover.jpg')
# add special tokens
icetk.add_special_tokens(['<start_of_image>', '<start_of_english>', '<start_of_chinese>'])
# transform \n
icetk.decode(icetk.encode('abc\nhi', ignore_linebreak=False))
# 'abc\nhi'
icetk.decode(icetk.encode('abc\nhi'))
# 'abc hi'
# discourage rare composed tokens
icetk.tokenize('//--------')
# ['▁//', '--------']
icetk.text_tokenizer.discourage_ids(range(125653,130000)) # or use icetk.text_tokenizer.discourage_tokens
icetk.tokenize('//--------')
# ['▁//', '-', '-', '-', '-', '-', '-', '-', '-']
FAQs
A unified tokenization tool for Images, Chinese and English.
We found that icetk demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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