Instructions to use ania3000/ossbert-morph-e-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ania3000/ossbert-morph-e-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ania3000/ossbert-morph-e-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ania3000/ossbert-morph-e-v2") model = AutoModelForTokenClassification.from_pretrained("ania3000/ossbert-morph-e-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 70862b30296588ec90fb53e2180d5a33be7a58578f66ac6d1af2fe946da62fd9
- Size of remote file:
- 420 MB
- SHA256:
- 8579594b4c4092b6057df4a9f5aff9d07bc193b8d66e40e0b92fa452abd3c1f5
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