tk
Turkmen Türkmençe
70,850 Words in vocabulary
4.95x Best compression
0.8902 Best isotropy
Sample text
Excerpts from Turkmen Wikipedia articles.
Wakalar Sebitler boýunça Tema boýunça <noinclude> Dünýä inenler Aradan çykanlar
Wakalar Sebitler boýunça Tema boýunça <noinclude> Dünýä inenler Aradan çykanlar
Seýdi etraby — Lebap welayatynyň bir etrabydyr. etraplary welaýaty welaýatyndaky...
Most common words
The 20 most frequently used words in Turkmen Wikipedia.
Interactive playground
Explore Turkmen interactively with browser-based demos.
Performance dashboard
Key metrics for all model types at a glance.
Quick start
Tokenizer
from wikilangs import tokenizer
tok = tokenizer('latest', 'tk', 32000)
tokens = tok.tokenize("Your text here")N-gram
from wikilangs import ngram
ng = ngram('latest', 'tk', gram_size=3)
score = ng.score("Your text here")Markov chain
from wikilangs import markov
mc = markov('latest', 'tk', depth=3)
text = mc.generate(length=50)Vocabulary
from wikilangs import vocabulary
vocab = vocabulary('latest', 'tk')
info = vocab.lookup("word")Embeddings
from wikilangs import embeddings
emb = embeddings('latest', 'tk', dimension=64)
vec = emb.embed_word("word")Available models
| 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 |
Model evaluation
Tokenizer performance
Compression ratios and token statistics across vocabulary sizes.
N-gram evaluation
Perplexity and entropy metrics across n-gram sizes.
Markov chain evaluation
Entropy and branching factor by context depth.
Vocabulary analysis
Word frequency distribution and Zipf's law analysis.
Embeddings evaluation
Isotropy and vector space quality metrics.
Full research report
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