Instructions to use tartuNLP/EstBERT_512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tartuNLP/EstBERT_512 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="tartuNLP/EstBERT_512")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("tartuNLP/EstBERT_512") model = AutoModelForMaskedLM.from_pretrained("tartuNLP/EstBERT_512") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e0273cdde1edf19c1494d8c7162f0ed85599656bfa5cdd6ac0efd3edc1a47a39
- Size of remote file:
- 498 MB
- SHA256:
- 2d04bf895bb465a0ff4fc97643f819a1bf251b80c3ac126b21d166d106b833b5
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