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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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{"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "model_max_length": 64, "max_len": 64}
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