Text Generation
fastText
Thai
wikilangs
nlp
tokenizer
embeddings
n-gram
markov
wikipedia
feature-extraction
sentence-similarity
tokenization
n-grams
markov-chain
text-mining
babelvec
vocabulous
vocabulary
monolingual
family-taikadai_southwestern
Instructions to use wikilangs/th with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/th with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/th", "model.bin")) - Notebooks
- Google Colab
- Kaggle
Download visualizations/performance_dashboard.png from wikilangs/th: direct link, hf CLI and curl.
- Browser
- Download file 359 kB
-
https://huggingface.co/wikilangs/th/resolve/main/visualizations/performance_dashboard.png
- Command line
-
hf download hf://wikilangs/th/visualizations/performance_dashboard.png
-
curl -L -o performance_dashboard.png https://huggingface.co/wikilangs/th/resolve/main/visualizations/performance_dashboard.png
359 kB

- Xet hash:
- f2088eabd412e87026ef9fa3118c64a17176537bbf4b3df0f973d9dc10ebabad
- Size of remote file:
- 359 kB
- SHA256:
- d1b352e3aa5b5c259fac711a6203e0882795091ad416134d7b65f0ba84a4d5b7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.