Instructions to use mrm8488/RuPERTa-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/RuPERTa-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mrm8488/RuPERTa-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mrm8488/RuPERTa-base") model = AutoModelForMaskedLM.from_pretrained("mrm8488/RuPERTa-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 963746da8990590b564006df7e3d69ea3b8d90edc2e03ca9e4c426046f25a801
- Size of remote file:
- 504 MB
- SHA256:
- 0dbe4e9f5bc35d5c2255774623e8606ce4bc98a176d61819f61166452f69d46d
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