sq

Albanian shqip

ISO 639-1: sq ISO 639-3: sqi M L
445,748 Words in vocabulary
4.62x Best compression
0.7903 Best isotropy

Sample text

Excerpts from Albanian Wikipedia articles.

është vendbanim në Ish Republikën Jugosllave të Maqedonisë. në komunën e Novacës
Mbi vitin 390 p.e.s.. Ngjarje Lindje Vdekje 390 p.e.s. p.e.s.
Shqiponja Perandorake e Lindjes (Aquila heliaca) është një Shqiponjë e madhe mbr...

Most common words

The 20 most frequently used words in Albanian Wikipedia.

Top 20 words in Albanian

Performance dashboard

Key metrics for all model types at a glance.

Performance dashboard for Albanian

Quick start

Tokenizer

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

N-gram

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

Markov chain

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

Vocabulary

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

Embeddings

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

Available models

Model Type Variants Description
Tokenizers8k, 16k, 32k, 64kBPE tokenizers with different vocabulary sizes
N-gram (Word)2, 3, 4, 5-gramWord-level language models
N-gram (Subword)2, 3, 4, 5-gramSubword-level language models
Markov (Word)Depth 1–5Word-level text generation
Markov (Subword)Depth 1–5Subword-level text generation
Vocabulary—Word dictionary with frequency and IDF
Embeddings32d, 64d, 128dPosition-aware word embeddings

Model evaluation

Tokenizer performance

Compression ratios and token statistics across vocabulary sizes.

Tokenizer compression

N-gram evaluation

Perplexity and entropy metrics across n-gram sizes.

N-gram perplexity

Markov chain evaluation

Entropy and branching factor by context depth.

Markov entropy

Vocabulary analysis

Word frequency distribution and Zipf's law analysis.

Zipf's law
Top 20 words

Embeddings evaluation

Isotropy and vector space quality metrics.

Embedding isotropy

Full research report

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