Instructions to use Tatiana239/lilt-ruroberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tatiana239/lilt-ruroberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Tatiana239/lilt-ruroberta")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Tatiana239/lilt-ruroberta") model = AutoModelForTokenClassification.from_pretrained("Tatiana239/lilt-ruroberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e24a3f660de4d9638de65d055faabe18316d4dd6f85ba7f4be98f0be41d47eb5
- Size of remote file:
- 521 MB
- SHA256:
- e1fb025b45df8580f3c4861f0508aae1277c01dc8fac688031130be0cd582477
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