Instructions to use language-ml-lab/postagger-azb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use language-ml-lab/postagger-azb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="language-ml-lab/postagger-azb")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("language-ml-lab/postagger-azb") model = AutoModelForTokenClassification.from_pretrained("language-ml-lab/postagger-azb") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3994ed6f00b7fb1ad514e1d2c5562c1450e92684f6fec55c71656a23d1808a58
- Size of remote file:
- 371 MB
- SHA256:
- 6a95c86f6776bbf2a7cbf2b2855e21d14f05a86715e2c982481f493ffc9d466c
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