Instructions to use sefa23/normalization-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sefa23/normalization-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="sefa23/normalization-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("sefa23/normalization-bert") model = AutoModelForMaskedLM.from_pretrained("sefa23/normalization-bert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 73b46cf3f8823b0e28cc7a5870406c8c2f7e3488c4d6c90ba75066694288fadc
- Size of remote file:
- 443 MB
- SHA256:
- a6a766d9f9c643d5835f88f9184a9d82bad7f902720b4cd8001ead15ce2387b8
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