Instructions to use EMBEDDIA/est-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EMBEDDIA/est-roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="EMBEDDIA/est-roberta")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("EMBEDDIA/est-roberta") model = AutoModelForMaskedLM.from_pretrained("EMBEDDIA/est-roberta") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3eda3126cce769d5053377b2f18c10f70f402b91c14e9263bcd8774533187f05
- Size of remote file:
- 467 MB
- SHA256:
- ae413ddc80e34b1339ef7f67727cb30a53e1ddd1926b921a6a97e9a7833d08f9
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