Instructions to use ania3000/kubert-morph with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ania3000/kubert-morph with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ania3000/kubert-morph")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ania3000/kubert-morph") model = AutoModelForTokenClassification.from_pretrained("ania3000/kubert-morph", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 67b284f6c6889dfb9a17587a581ee04787a180db08a9968d0c07e30a499ab6cf
- Size of remote file:
- 5.84 kB
- SHA256:
- e89a44bed0b1c33f530040a152931cde4672ac117f0fd9fbacd636381475b417
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