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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 03b32dd33a7a665ce6c3af1170f8ef901072ef19e5f72f72403db5d3280cd6d6
- Size of remote file:
- 5.84 kB
- SHA256:
- 0a772336e6dab3e420e97411d426a6bcb51e0fa5e8ec967cb5555cb2ddc2b4b5
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