Instructions to use perplexity-correlations/fasttext-lambada-es-target with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use perplexity-correlations/fasttext-lambada-es-target with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("perplexity-correlations/fasttext-lambada-es-target", "model.bin")) - Notebooks
- Google Colab
- Kaggle
Download lambada_es_target.bin from perplexity-correlations/fasttext-lambada-es-target: direct link, hf CLI and curl.
- Browser
- Download file 3.87 GB
-
https://huggingface.co/perplexity-correlations/fasttext-lambada-es-target/resolve/main/lambada_es_target.bin
- Command line
-
hf download hf://perplexity-correlations/fasttext-lambada-es-target/lambada_es_target.bin
-
curl -L -o lambada_es_target.bin https://huggingface.co/perplexity-correlations/fasttext-lambada-es-target/resolve/main/lambada_es_target.bin
3.87 GB
- Xet hash:
- c9e0cf5c799e756735f2d86be5db32fffefa5704cc8d312db7079246201a6a92
- Size of remote file:
- 3.87 GB
- SHA256:
- 3cdc99472585bad9595b60f12aca6af1a1eeb3915d4421f1f345b539e661fd26
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.