mni

Manipuri ꯃꯤꯇꯩ ꯂꯣꯟ

ISO 639-3: mni I L

35,928 Words in vocabulary

4.32x Best compression

0.6424 Best isotropy

Sample text

Excerpts from Manipuri Wikipedia articles.

ꯂꯥꯢꯔꯤꯛ ꯄꯔꯤꯡ (ꯕꯨꯛ ꯁꯤꯔꯤꯁ) ꯑꯁꯤ ꯑꯉꯥꯡꯁꯤꯡꯒꯤ ꯂꯥꯢꯔꯤꯛꯁꯤꯡꯒꯤ ꯃꯅꯨꯡꯗꯒꯤ ꯑꯃꯅꯤ ꯫ ꯃꯁꯤꯁꯨ ꯌꯦꯡꯕꯤꯌꯨ ꯃ...

ꯃꯁꯤꯡ ꯑꯁꯤ ꯗꯒꯤ ꯍꯦꯟꯅ ꯆꯥꯎꯕ ꯃꯁꯤꯡ ꯑꯃꯅꯤ꯫ ꯃꯁꯤꯗꯒꯤ ꯃꯁꯤꯡ ꯱ ꯍꯦꯟꯅ ꯆꯥꯎꯕ ꯃꯁꯤꯡ ꯗꯤ ꯅꯤ꯫ ꯃꯇꯦꯡ ꯂꯧꯔꯛꯐ...

ꯑꯂꯤ ꯐꯥꯓꯜ ꯑꯁꯤ ꯏꯟꯗꯤꯌꯥꯒꯤ ꯍꯤꯟꯗꯤ ꯂꯣꯟꯒꯤ ꯕꯣꯜꯂꯤꯋꯨꯗ (ꯍꯤꯟꯗꯤ ꯃꯃꯤ ꯀꯨꯝꯃꯩ)ꯒꯤ ꯁꯛꯇꯝ ꯂꯥꯡꯕ ꯁꯤꯟꯂꯣꯢ ...

The 20 most frequently used words in Manipuri Wikipedia.

Explore Manipuri interactively with browser-based demos.

Key metrics for all model types at a glance.

from wikilangs import tokenizer
tok = tokenizer('latest', 'mni', 32000)
tokens = tok.tokenize("Your text here")

from wikilangs import ngram
ng = ngram('latest', 'mni', gram_size=3)
score = ng.score("Your text here")

from wikilangs import markov
mc = markov('latest', 'mni', depth=3)
text = mc.generate(length=50)

from wikilangs import vocabulary
vocab = vocabulary('latest', 'mni')
info = vocab.lookup("word")

from wikilangs import embeddings
emb = embeddings('latest', 'mni', dimension=64)
vec = emb.embed_word("word")

Model Type	Variants	Description
Tokenizers	8k, 16k, 32k, 64k	BPE tokenizers with different vocabulary sizes
N-gram (Word)	2, 3, 4, 5-gram	Word-level language models
N-gram (Subword)	2, 3, 4, 5-gram	Subword-level language models
Markov (Word)	Depth 1–5	Word-level text generation
Markov (Subword)	Depth 1–5	Subword-level text generation
Vocabulary	—	Word dictionary with frequency and IDF
Embeddings	32d, 64d, 128d	Position-aware word embeddings