Instructions to use fav-kky/FERNET-News_sk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fav-kky/FERNET-News_sk with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="fav-kky/FERNET-News_sk")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("fav-kky/FERNET-News_sk") model = AutoModelForMaskedLM.from_pretrained("fav-kky/FERNET-News_sk") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9eabf38069908bc5b15eae5755a8860b97e5cbf1b6e5743eaba1f75718d18033
- Size of remote file:
- 498 MB
- SHA256:
- cb285c589cc5455fed884c9e2ede92addcc808d403463e0831b01b5f17b8601c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.