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414M tokens

  1. 73M hy wikipedia
  2. 341M arlis database

74951 unique words

3-5 ngrams

5 window length

300 embedding dim

skipgram

minimum number of words 150

100 epochs, 0.05 start lr

26 hours on 20 xeon gold cores

How to use

  1. Install fastText
pip install fasttext-wheel
  1. Import fastText in python
import fasttext
from huggingface_hub import hf_hub_download

model_path = hf_hub_download(local_dir=".",
                             repo_id="armvectores/wikipedia_arlis_tokens_fasttextskipgram_300_5",
                             filename="model.bin")
model = fasttext.load_model(model_path)
  1. Examples of usage
word = 'զենքեր'
print(model.get_nearest_neighbors(word))
print(model.get_sentence_vector(word))
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Dataset used to train armvectores/wikipedia_arlis_tokens_fasttextskipgram_300_5