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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("sefa23/normalization-bert") model = AutoModelForMaskedLM.from_pretrained("sefa23/normalization-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from sefa23/normalization-bert: direct link, hf CLI and curl.
- Browser
- Download file 200 Bytes
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https://huggingface.co/sefa23/normalization-bert/resolve/main/README.md
- Command line
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hf download hf://sefa23/normalization-bert/README.md
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curl -L -o README.md https://huggingface.co/sefa23/normalization-bert/resolve/main/README.md
200 Bytes
metadata
widget:
- text: eve varınca beni [MASK].
example_title: Örnek 1
- text: bugün okulda [MASK] gördüm.
example_title: Örnek 2
license: mit
language:
- tr
pipeline_tag: fill-mask