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
- Xet hash:
- 778415cf1b9f25493659a93f00829269004395f30ac1ac029f1d48c0bedd5e4b
- Size of remote file:
- 374 MB
- SHA256:
- 329c6f237ec91506c2c59aba947fd75267403f6ed72126289ecd81d29cac43c2
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