Instructions to use language-ml-lab/AzerBert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use language-ml-lab/AzerBert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="language-ml-lab/AzerBert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("language-ml-lab/AzerBert") model = AutoModelForMaskedLM.from_pretrained("language-ml-lab/AzerBert") - Notebooks
- Google Colab
- Kaggle
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Parent(s): 7ec8ca1
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tokenizer_config.json
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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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