Instructions to use facebook/fasttext-nah-vectors with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use facebook/fasttext-nah-vectors with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("facebook/fasttext-nah-vectors", "model.bin")) - Notebooks
- Google Colab
- Kaggle
Download model.bin from facebook/fasttext-nah-vectors: direct link, hf CLI and curl.
- Browser
- Download file 2.68 GB
-
https://huggingface.co/facebook/fasttext-nah-vectors/resolve/main/model.bin
- Command line
-
hf download hf://facebook/fasttext-nah-vectors/model.bin
-
curl -L -o model.bin https://huggingface.co/facebook/fasttext-nah-vectors/resolve/main/model.bin
2.68 GB
- Xet hash:
- 8cb728db49aeed408a0b53e042b2177809e06fc47da54a84e03b77cf5087f762
- Size of remote file:
- 2.68 GB
- SHA256:
- 60f6db5ef1f0343462f6260ae0be7b5cf9b5d734ec5871197d7e6f2eedbcf794
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.