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:
- 8e752ad99e8fd11f118562184c0fbf5f75fb097b9cb6318ced5288868cebaf94
- Size of remote file:
- 710 MB
- SHA256:
- 4630b737cb929e82103c1fce9e5aded7f6a6c10200a166e5c251a0669f90470c
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