Instructions to use IMJONEZZ/SlovenBERTcina with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IMJONEZZ/SlovenBERTcina with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="IMJONEZZ/SlovenBERTcina")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("IMJONEZZ/SlovenBERTcina") model = AutoModelForMaskedLM.from_pretrained("IMJONEZZ/SlovenBERTcina") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5e4a618b034c6c5444c75183cf02b823c4b3869681970ba2d5107fd2cc2fc06b
- Size of remote file:
- 343 MB
- SHA256:
- 7289c7b79e9c6dc203509bbd74cb5b2665832862fc4248ad9f2e70f9689fe7d7
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