Instructions to use nsadeq/InformBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nsadeq/InformBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nsadeq/InformBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nsadeq/InformBERT") model = AutoModelForMaskedLM.from_pretrained("nsadeq/InformBERT") - Notebooks
- Google Colab
- Kaggle
Upload 3 files
Browse files- tokenizer.json +0 -0
- tokenizer_config.json +3 -0
- vocab.txt +0 -0
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