issai / tilmash

Tilmash

Tilmash was fine-tuned using Facebook’s NLLB model to enable machine translation for four languages—Kazakh, Russian, English, and Turkish. Below are the BLEU | chrF results of evaluating Tilmash on the FLoRes and KazParC test datasets.

Model Sources

• Repository: https://github.com/IS2AI/KazParC
• Paper: KazParC: Kazakh Parallel Corpus for Machine Translation
• Demo: Tilmash Demo

How to Get Started with the Model

You can use this model with the Transformers pipeline for translation.

from transformers import AutoModelForSeq2SeqLM, AutoTokenizer, TranslationPipeline

model = AutoModelForSeq2SeqLM.from_pretrained('issai/tilmash')
tokenizer = AutoTokenizer.from_pretrained("issai/tilmash")

# for src_lang and tgt_lang choose from kaz_Cyrl (Kazakh), rus_Cyrl (Russian), eng_Latn (English), tur_Latn (Turkish)
tilmash = TranslationPipeline(model = model, tokenizer = tokenizer, src_lang = "kaz_Cyrl", tgt_lang = "eng_Latn", max_length = 1000)

print(tilmash("Қазақстан — Шығыс Еуропа мен Орталық Азияда орналасқан мемлекет."))
# [{'translation_text': 'Kazakhstan is a country located in Eastern Europe and Central Asia.'}]