Instructions to use mrm8488/RuPERTa-base-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/RuPERTa-base-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mrm8488/RuPERTa-base-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mrm8488/RuPERTa-base-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("mrm8488/RuPERTa-base-finetuned-ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44d40a93ed8d3898d93ee62d946eb1d9b4b6100f2d8a504b8240109c89db66e2
- Size of remote file:
- 502 MB
- SHA256:
- 766066c04f6286a871cb3815c7809b05265b0c446923c9c65eb109332ecd65b8
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