Text Generation
fastText
Gothic
wikilangs
nlp
tokenizer
embeddings
n-gram
markov
wikipedia
feature-extraction
sentence-similarity
tokenization
n-grams
markov-chain
text-mining
babelvec
vocabulous
vocabulary
monolingual
family-germanic_historical
Instructions to use wikilangs/got with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/got with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/got", "model.bin")) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b5c3c0ef703819c094fd05923f6cf09c3e9f4bbcf270d3220613e97257b2f46b
- Size of remote file:
- 695 kB
- SHA256:
- aa3c9dea5966c98e41ad0d350dfe7c903f2de25905c61b8c26bc7c6494e9e6e0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.