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:
- 2cbff6492182fec1357f6c2d6214c8d1eee51c6d3d682b2e2b8515f92b6ca849
- Size of remote file:
- 653 MB
- SHA256:
- 999f0bca627e738de26b31b5fc077d80dd08a00278d43a2bb71dc1814d2304db
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