Instructions to use fav-kky/FERNET-News with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fav-kky/FERNET-News with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="fav-kky/FERNET-News")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("fav-kky/FERNET-News") model = AutoModelForMaskedLM.from_pretrained("fav-kky/FERNET-News", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 611cd190745fda2dba45247d03ff4c30aadaec7083479660fa6bd80a0fa94a13
- Size of remote file:
- 498 MB
- SHA256:
- 19335fa81f75dcae70e3e25819e5cb93f3ccc7971258b1434457707d9b241af3
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